R/indbcomp.R
In chrisaberson/BetterReg: Better Statistics for OLS and Binomial Logistic Regression
Defines functions
indbcomp
Documented in
indbcomp
#'Comparing Independent Coefficients in Multiple Regression
#'@param model1 Summary of first model (see example for how to summarize)
#'@param model2 Summary of second model (see example for how to summarize)
#'@param comps Type of comparison. "abs" - absolute value of coefficient
#'@param pred Number of predictors
#'@examples
#'y_1<-rnorm(200); x1_1<-rnorm(200); x2_1<-rnorm(200)
#'y_2<-rnorm(200); x1_2<-rnorm(200);x2_2<-rnorm(200)
#'df1<-as.data.frame(cbind(y_1, x1_1,x2_1))
#'df2<-as.data.frame(cbind(y_2, x1_2,x2_2))
#'model1_2<-summary(lm(y_1~x1_1+x2_1, data=df1))
#'model2_2<-summary(lm(y_2~x1_2+x2_2, data=df2))
#'indbcomp(model1 = model1_2, model2 = model2_2, comps="abs", pred=2)
#'@return Comparing Independent Coefficients in Multiple Regression
#'@export
#'
indbcomp<-function(model1=NULL, model2=NULL, comps="abs", pred=NULL)
{
if ((pred =="2") && (comps=="abs")){
b1_1<-(model1$coefficients)[2,4]
b2_1<-(model1$coefficients)[3,4]
b1_2<-(model2$coefficients)[2,4]
b2_2<-(model2$coefficients)[3,4]
seb1_1<-model1$coefficients[2,2]
seb2_1<-model1$coefficients[3,2]
seb1_2<-model2$coefficients[2,2]
seb2_2<-model2$coefficients[3,2]
sebb1<-((seb1_1^2)+(seb2_1^2))^.5
sebb2<-((seb1_2^2)+(seb2_2^2))^.5
t1<-abs(abs(b1_1)-abs(b1_2))/sebb1
t2<-abs(abs(b2_1)-abs(b2_2))/sebb2
df1<-model1$df[2]+model2$df[2]
df2<-model2$df[2]
p1<-2*round(1-(pt(q=abs(t1), df=df1, lower.tail=TRUE)),3)
p2<-2*round(1-(pt(q=abs(t2), df=df2, lower.tail=TRUE)),3)
t1<-round((t1),3)
t2<-round((t2),3)
message("Predictor 1: "," t = ", t1,", p = ", p1)
message("Predictor 2: "," t = ", t2,", p = ", p2)
}
if ((pred =="3") && (comps=="abs")){
b1_1<-(model1$coefficients)[2,4]
b2_1<-(model1$coefficients)[3,4]
b3_1<-(model1$coefficients)[4,4]
b1_2<-(model2$coefficients)[2,4]
b2_2<-(model2$coefficients)[3,4]
b3_2<-(model2$coefficients)[4,4]
seb1_1<-model1$coefficients[2,2]
seb2_1<-model1$coefficients[3,2]
seb3_1<-model1$coefficients[4,2]
seb1_2<-model2$coefficients[2,2]
seb2_2<-model2$coefficients[3,2]
seb3_2<-model2$coefficients[4,2]
sebb1<-((seb1_1^2)+(seb1_2^2))^.5
sebb2<-((seb2_1^2)+(seb2_2^2))^.5
sebb3<-((seb3_1^2)+(seb3_2^2))^.5
t1<-abs(abs(b1_1)-abs(b1_2))/sebb1
t2<-abs(abs(b2_1)-abs(b2_2))/sebb2
t3<-abs(abs(b3_1)-abs(b3_2))/sebb3
df1<-model1$df[2]+model2$df[2]
p1<-2*round(1-(pt(q=abs(t1), df=df1, lower.tail=TRUE)),3)
p2<-2*round(1-(pt(q=abs(t2), df=df1, lower.tail=TRUE)),3)
p3<-2*round(1-(pt(q=abs(t3), df=df1, lower.tail=TRUE)),3)
t1<-round((t1),3)
t2<-round((t2),3)
t3<-round((t3),3)
message("Predictor 1: "," t = ", t1,", p = ", p1)
message("Predictor 2: "," t = ", t2,", p = ", p2)
message("Predictor 3: "," t = ", t3,", p = ", p3)
}
if ((pred =="4") && (comps=="abs")){
b1_1<-(model1$coefficients)[2,4]
b2_1<-(model1$coefficients)[3,4]
b3_1<-(model1$coefficients)[4,4]
b4_1<-(model1$coefficients)[5,4]
b1_2<-(model2$coefficients)[2,4]
b2_2<-(model2$coefficients)[3,4]
b3_2<-(model2$coefficients)[4,4]
b4_2<-(model2$coefficients)[5,4]
seb1_1<-model1$coefficients[2,2]
seb2_1<-model1$coefficients[3,2]
seb3_1<-model1$coefficients[4,2]
seb4_1<-model1$coefficients[5,2]
seb1_2<-model2$coefficients[2,2]
seb2_2<-model2$coefficients[3,2]
seb3_2<-model2$coefficients[4,2]
seb4_2<-model2$coefficients[5,2]
sebb1<-((seb1_1^2)+(seb1_2^2))^.5
sebb2<-((seb2_1^2)+(seb2_2^2))^.5
sebb3<-((seb3_1^2)+(seb3_2^2))^.5
sebb4<-((seb4_1^2)+(seb4_2^2))^.5
t1<-abs(abs(b1_1)-abs(b1_2))/sebb1
t2<-abs(abs(b2_1)-abs(b2_2))/sebb2
t3<-abs(abs(b3_1)-abs(b3_2))/sebb3
t4<-abs(abs(b4_1)-abs(b4_2))/sebb4
df1<-model1$df[2]+model2$df[2]
p1<-2*round(1-(pt(q=abs(t1), df=df1, lower.tail=TRUE)),3)
p2<-2*round(1-(pt(q=abs(t2), df=df1, lower.tail=TRUE)),3)
p3<-2*round(1-(pt(q=abs(t3), df=df1, lower.tail=TRUE)),3)
p4<-2*round(1-(pt(q=abs(t4), df=df1, lower.tail=TRUE)),3)
t1<-round((t1),3)
t2<-round((t2),3)
t3<-round((t3),3)
t4<-round((t4),3)
message("Predictor 1: "," t = ", t1,", p = ", p1)
message("Predictor 2: "," t = ", t2,", p = ", p2)
message("Predictor 3: "," t = ", t3,", p = ", p3)
message("Predictor 4: "," t = ", t4,", p = ", p4)
}
if ((pred =="5") && (comps=="abs")){
b1_1<-(model1$coefficients)[2,4]
b2_1<-(model1$coefficients)[3,4]
b3_1<-(model1$coefficients)[4,4]
b4_1<-(model1$coefficients)[5,4]
b5_1<-(model1$coefficients)[6,4]
b1_2<-(model2$coefficients)[2,4]
b2_2<-(model2$coefficients)[3,4]
b3_2<-(model2$coefficients)[4,4]
b4_2<-(model2$coefficients)[5,4]
b5_2<-(model2$coefficients)[6,4]
seb1_1<-model1$coefficients[2,2]
seb2_1<-model1$coefficients[3,2]
seb3_1<-model1$coefficients[4,2]
seb4_1<-model1$coefficients[5,2]
seb5_1<-model1$coefficients[6,2]
seb1_2<-model2$coefficients[2,2]
seb2_2<-model2$coefficients[3,2]
seb3_2<-model2$coefficients[4,2]
seb4_2<-model2$coefficients[5,2]
seb5_2<-model2$coefficients[6,2]
sebb1<-((seb1_1^2)+(seb1_2^2))^.5
sebb2<-((seb2_1^2)+(seb2_2^2))^.5
sebb3<-((seb3_1^2)+(seb3_2^2))^.5
sebb4<-((seb4_1^2)+(seb4_2^2))^.5
sebb5<-((seb5_1^2)+(seb5_2^2))^.5
t1<-abs(abs(b1_1)-abs(b1_2))/sebb1
t2<-abs(abs(b2_1)-abs(b2_2))/sebb2
t3<-abs(abs(b3_1)-abs(b3_2))/sebb3
t4<-abs(abs(b4_1)-abs(b4_2))/sebb4
t5<-abs(abs(b5_1)-abs(b5_2))/sebb5
df1<-model1$df[2]+model2$df[2]
p1<-2*round(1-(pt(q=abs(t1), df=df1, lower.tail=TRUE)),3)
p2<-2*round(1-(pt(q=abs(t2), df=df1, lower.tail=TRUE)),3)
p3<-2*round(1-(pt(q=abs(t3), df=df1, lower.tail=TRUE)),3)
p4<-2*round(1-(pt(q=abs(t4), df=df1, lower.tail=TRUE)),3)
p5<-2*round(1-(pt(q=abs(t5), df=df1, lower.tail=TRUE)),3)
t1<-round((t1),3)
t2<-round((t2),3)
t3<-round((t3),3)
t4<-round((t4),3)
t5<-round((t5),3)
message("Predictor 1: "," t = ", t1,", p = ", p1)
message("Predictor 2: "," t = ", t2,", p = ", p2)
message("Predictor 3: "," t = ", t3,", p = ", p3)
message("Predictor 4: "," t = ", t4,", p = ", p4)
message("Predictor 5: "," t = ", t5,", p = ", p5)
}
if ((pred =="6") && (comps=="abs")){
b1_1<-(model1$coefficients)[2,4]
b2_1<-(model1$coefficients)[3,4]
b3_1<-(model1$coefficients)[4,4]
b4_1<-(model1$coefficients)[5,4]
b5_1<-(model1$coefficients)[6,4]
b6_1<-(model1$coefficients)[7,4]
b1_2<-(model2$coefficients)[2,4]
b2_2<-(model2$coefficients)[3,4]
b3_2<-(model2$coefficients)[4,4]
b4_2<-(model2$coefficients)[5,4]
b5_2<-(model2$coefficients)[6,4]
b6_2<-(model2$coefficients)[7,4]
seb1_1<-model1$coefficients[2,2]
seb2_1<-model1$coefficients[3,2]
seb3_1<-model1$coefficients[4,2]
seb4_1<-model1$coefficients[5,2]
seb5_1<-model1$coefficients[6,2]
seb6_1<-model1$coefficients[7,2]
seb1_2<-model2$coefficients[2,2]
seb2_2<-model2$coefficients[3,2]
seb3_2<-model2$coefficients[4,2]
seb4_2<-model2$coefficients[5,2]
seb5_2<-model2$coefficients[6,2]
seb6_2<-model2$coefficients[7,2]
sebb1<-((seb1_1^2)+(seb1_2^2))^.5
sebb2<-((seb2_1^2)+(seb2_2^2))^.5
sebb3<-((seb3_1^2)+(seb3_2^2))^.5
sebb4<-((seb4_1^2)+(seb4_2^2))^.5
sebb5<-((seb5_1^2)+(seb5_2^2))^.5
sebb6<-((seb6_1^2)+(seb6_2^2))^.5
t1<-abs(abs(b1_1)-abs(b1_2))/sebb1
t2<-abs(abs(b2_1)-abs(b2_2))/sebb2
t3<-abs(abs(b3_1)-abs(b3_2))/sebb3
t4<-abs(abs(b4_1)-abs(b4_2))/sebb4
t5<-abs(abs(b5_1)-abs(b5_2))/sebb5
t6<-abs(abs(b6_1)-abs(b6_2))/sebb6
df1<-model1$df[2]+model2$df[2]
p1<-2*round(1-(pt(q=abs(t1), df=df1, lower.tail=TRUE)),3)
p2<-2*round(1-(pt(q=abs(t2), df=df1, lower.tail=TRUE)),3)
p3<-2*round(1-(pt(q=abs(t3), df=df1, lower.tail=TRUE)),3)
p4<-2*round(1-(pt(q=abs(t4), df=df1, lower.tail=TRUE)),3)
p5<-2*round(1-(pt(q=abs(t5), df=df1, lower.tail=TRUE)),3)
p6<-2*round(1-(pt(q=abs(t6), df=df1, lower.tail=TRUE)),3)
t1<-round((t1),3)
t2<-round((t2),3)
t3<-round((t3),3)
t4<-round((t4),3)
t5<-round((t5),3)
t6<-round((t6),3)
message("Predictor 1: "," t = ", t1,", p = ", p1)
message("Predictor 2: "," t = ", t2,", p = ", p2)
message("Predictor 3: "," t = ", t3,", p = ", p3)
message("Predictor 4: "," t = ", t4,", p = ", p4)
message("Predictor 5: "," t = ", t5,", p = ", p5)
message("Predictor 6: "," t = ", t6,", p = ", p6)
}
if ((pred =="7") && (comps=="abs")){
b1_1<-(model1$coefficients)[2,4]
b2_1<-(model1$coefficients)[3,4]
b3_1<-(model1$coefficients)[4,4]
b4_1<-(model1$coefficients)[5,4]
b5_1<-(model1$coefficients)[6,4]
b6_1<-(model1$coefficients)[7,4]
b7_1<-(model1$coefficients)[8,4]
b1_2<-(model2$coefficients)[2,4]
b2_2<-(model2$coefficients)[3,4]
b3_2<-(model2$coefficients)[4,4]
b4_2<-(model2$coefficients)[5,4]
b5_2<-(model2$coefficients)[6,4]
b6_2<-(model2$coefficients)[7,4]
b7_2<-(model2$coefficients)[8,4]
seb1_1<-model1$coefficients[2,2]
seb2_1<-model1$coefficients[3,2]
seb3_1<-model1$coefficients[4,2]
seb4_1<-model1$coefficients[5,2]
seb5_1<-model1$coefficients[6,2]
seb6_1<-model1$coefficients[7,2]
seb7_1<-model1$coefficients[8,2]
seb1_2<-model2$coefficients[2,2]
seb2_2<-model2$coefficients[3,2]
seb3_2<-model2$coefficients[4,2]
seb4_2<-model2$coefficients[5,2]
seb5_2<-model2$coefficients[6,2]
seb6_2<-model2$coefficients[7,2]
seb7_2<-model2$coefficients[8,2]
sebb1<-((seb1_1^2)+(seb1_2^2))^.5
sebb2<-((seb2_1^2)+(seb2_2^2))^.5
sebb3<-((seb3_1^2)+(seb3_2^2))^.5
sebb4<-((seb4_1^2)+(seb4_2^2))^.5
sebb5<-((seb5_1^2)+(seb5_2^2))^.5
sebb6<-((seb6_1^2)+(seb6_2^2))^.5
sebb7<-((seb7_1^2)+(seb7_2^2))^.5
t1<-abs(abs(b1_1)-abs(b1_2))/sebb1
t2<-abs(abs(b2_1)-abs(b2_2))/sebb2
t3<-abs(abs(b3_1)-abs(b3_2))/sebb3
t4<-abs(abs(b4_1)-abs(b4_2))/sebb4
t5<-abs(abs(b5_1)-abs(b5_2))/sebb5
t6<-abs(abs(b6_1)-abs(b6_2))/sebb6
t7<-abs(abs(b7_1)-abs(b7_2))/sebb7
df1<-model1$df[2]+model2$df[2]
p1<-2*round(1-(pt(q=abs(t1), df=df1, lower.tail=TRUE)),3)
p2<-2*round(1-(pt(q=abs(t2), df=df1, lower.tail=TRUE)),3)
p3<-2*round(1-(pt(q=abs(t3), df=df1, lower.tail=TRUE)),3)
p4<-2*round(1-(pt(q=abs(t4), df=df1, lower.tail=TRUE)),3)
p5<-2*round(1-(pt(q=abs(t5), df=df1, lower.tail=TRUE)),3)
p6<-2*round(1-(pt(q=abs(t6), df=df1, lower.tail=TRUE)),3)
p7<-2*round(1-(pt(q=abs(t7), df=df1, lower.tail=TRUE)),3)
t1<-round((t1),3)
t2<-round((t2),3)
t3<-round((t3),3)
t4<-round((t4),3)
t5<-round((t5),3)
t6<-round((t6),3)
t7<-round((t7),3)
message("Predictor 1: "," t = ", t1,", p = ", p1)
message("Predictor 2: "," t = ", t2,", p = ", p2)
message("Predictor 3: "," t = ", t3,", p = ", p3)
message("Predictor 4: "," t = ", t4,", p = ", p4)
message("Predictor 5: "," t = ", t5,", p = ", p5)
message("Predictor 6: "," t = ", t6,", p = ", p6)
message("Predictor 7: "," t = ", t7,", p = ", p7)
}
if ((pred =="8") && (comps=="abs")){
b1_1<-(model1$coefficients)[2,4]
b2_1<-(model1$coefficients)[3,4]
b3_1<-(model1$coefficients)[4,4]
b4_1<-(model1$coefficients)[5,4]
b5_1<-(model1$coefficients)[6,4]
b6_1<-(model1$coefficients)[7,4]
b7_1<-(model1$coefficients)[8,4]
b8_1<-(model1$coefficients)[9,4]
b1_2<-(model2$coefficients)[2,4]
b2_2<-(model2$coefficients)[3,4]
b3_2<-(model2$coefficients)[4,4]
b4_2<-(model2$coefficients)[5,4]
b5_2<-(model2$coefficients)[6,4]
b6_2<-(model2$coefficients)[7,4]
b7_2<-(model2$coefficients)[8,4]
b8_2<-(model2$coefficients)[9,4]
seb1_1<-model1$coefficients[2,2]
seb2_1<-model1$coefficients[3,2]
seb3_1<-model1$coefficients[4,2]
seb4_1<-model1$coefficients[5,2]
seb5_1<-model1$coefficients[6,2]
seb6_1<-model1$coefficients[7,2]
seb7_1<-model1$coefficients[8,2]
seb8_1<-model1$coefficients[9,2]
seb1_2<-model2$coefficients[2,2]
seb2_2<-model2$coefficients[3,2]
seb3_2<-model2$coefficients[4,2]
seb4_2<-model2$coefficients[5,2]
seb5_2<-model2$coefficients[6,2]
seb6_2<-model2$coefficients[7,2]
seb7_2<-model2$coefficients[8,2]
seb8_2<-model2$coefficients[9,2]
sebb1<-((seb1_1^2)+(seb1_2^2))^.5
sebb2<-((seb2_1^2)+(seb2_2^82))^.5
sebb3<-((seb3_1^2)+(seb3_2^2))^.5
sebb4<-((seb4_1^2)+(seb4_2^2))^.5
sebb5<-((seb5_1^2)+(seb5_2^2))^.5
sebb6<-((seb6_1^2)+(seb6_2^2))^.5
sebb7<-((seb7_1^2)+(seb7_2^2))^.5
sebb8<-((seb8_1^2)+(seb8_2^2))^.5
t1<-abs(abs(b1_1)-abs(b1_2))/sebb1
t2<-abs(abs(b2_1)-abs(b2_2))/sebb2
t3<-abs(abs(b3_1)-abs(b3_2))/sebb3
t4<-abs(abs(b4_1)-abs(b4_2))/sebb4
t5<-abs(abs(b5_1)-abs(b5_2))/sebb5
t6<-abs(abs(b6_1)-abs(b6_2))/sebb6
t7<-abs(abs(b7_1)-abs(b7_2))/sebb7
t8<-abs(abs(b8_1)-abs(b8_2))/sebb8
df1<-model1$df[2]+model2$df[2]
p1<-2*round(1-(pt(q=abs(t1), df=df1, lower.tail=TRUE)),3)
p2<-2*round(1-(pt(q=abs(t2), df=df1, lower.tail=TRUE)),3)
p3<-2*round(1-(pt(q=abs(t3), df=df1, lower.tail=TRUE)),3)
p4<-2*round(1-(pt(q=abs(t4), df=df1, lower.tail=TRUE)),3)
p5<-2*round(1-(pt(q=abs(t5), df=df1, lower.tail=TRUE)),3)
p6<-2*round(1-(pt(q=abs(t6), df=df1, lower.tail=TRUE)),3)
p7<-2*round(1-(pt(q=abs(t7), df=df1, lower.tail=TRUE)),3)
p8<-2*round(1-(pt(q=abs(t8), df=df1, lower.tail=TRUE)),3)
t1<-round((t1),3)
t2<-round((t2),3)
t3<-round((t3),3)
t4<-round((t4),3)
t5<-round((t5),3)
t6<-round((t6),3)
t7<-round((t7),3)
t8<-round((t8),3)
message("Predictor 1: "," t = ", t1,", p = ", p1)
message("Predictor 2: "," t = ", t2,", p = ", p2)
message("Predictor 3: "," t = ", t3,", p = ", p3)
message("Predictor 4: "," t = ", t4,", p = ", p4)
message("Predictor 5: "," t = ", t5,", p = ", p5)
message("Predictor 6: "," t = ", t6,", p = ", p6)
message("Predictor 7: "," t = ", t7,", p = ", p7)
message("Predictor 8: "," t = ", t8,", p = ", p8)
}
if ((pred =="9") && (comps=="abs")){
b1_1<-(model1$coefficients)[2,4]
b2_1<-(model1$coefficients)[3,4]
b3_1<-(model1$coefficients)[4,4]
b4_1<-(model1$coefficients)[5,4]
b5_1<-(model1$coefficients)[6,4]
b6_1<-(model1$coefficients)[7,4]
b7_1<-(model1$coefficients)[8,4]
b8_1<-(model1$coefficients)[9,4]
b9_1<-(model1$coefficients)[10,4]
b1_2<-(model2$coefficients)[2,4]
b2_2<-(model2$coefficients)[3,4]
b3_2<-(model2$coefficients)[4,4]
b4_2<-(model2$coefficients)[5,4]
b5_2<-(model2$coefficients)[6,4]
b6_2<-(model2$coefficients)[7,4]
b7_2<-(model2$coefficients)[8,4]
b8_2<-(model2$coefficients)[9,4]
b9_2<-(model2$coefficients)[10,4]
seb1_1<-model1$coefficients[2,2]
seb2_1<-model1$coefficients[3,2]
seb3_1<-model1$coefficients[4,2]
seb4_1<-model1$coefficients[5,2]
seb5_1<-model1$coefficients[6,2]
seb6_1<-model1$coefficients[7,2]
seb7_1<-model1$coefficients[8,2]
seb8_1<-model1$coefficients[9,2]
seb9_1<-model1$coefficients[10,2]
seb1_2<-model2$coefficients[2,2]
seb2_2<-model2$coefficients[3,2]
seb3_2<-model2$coefficients[4,2]
seb4_2<-model2$coefficients[5,2]
seb5_2<-model2$coefficients[6,2]
seb6_2<-model2$coefficients[7,2]
seb7_2<-model2$coefficients[8,2]
seb8_2<-model2$coefficients[9,2]
seb9_2<-(model2$coefficients)[10,2]
sebb1<-((seb1_1^2)+(seb1_2^2))^.5
sebb2<-((seb2_1^2)+(seb2_2^2))^.5
sebb3<-((seb3_1^2)+(seb3_2^2))^.5
sebb4<-((seb4_1^2)+(seb4_2^2))^.5
sebb5<-((seb5_1^2)+(seb5_2^2))^.5
sebb6<-((seb6_1^2)+(seb6_2^2))^.5
sebb7<-((seb7_1^2)+(seb7_2^2))^.5
sebb8<-((seb8_1^2)+(seb8_2^2))^.5
sebb9<-((seb9_1^2)+(seb9_2^2))^.5
t1<-abs(abs(b1_1)-abs(b1_2))/sebb1
t2<-abs(abs(b2_1)-abs(b2_2))/sebb2
t3<-abs(abs(b3_1)-abs(b3_2))/sebb3
t4<-abs(abs(b4_1)-abs(b4_2))/sebb4
t5<-abs(abs(b5_1)-abs(b5_2))/sebb5
t6<-abs(abs(b6_1)-abs(b6_2))/sebb6
t7<-abs(abs(b7_1)-abs(b7_2))/sebb7
t8<-abs(abs(b8_1)-abs(b8_2))/sebb8
t9<-abs(abs(b9_1)-abs(b9_2))/sebb9
df1<-model1$df[2]+model2$df[2]
p1<-2*round(1-(pt(q=abs(t1), df=df1, lower.tail=TRUE)),3)
p2<-2*round(1-(pt(q=abs(t2), df=df1, lower.tail=TRUE)),3)
p3<-2*round(1-(pt(q=abs(t3), df=df1, lower.tail=TRUE)),3)
p4<-2*round(1-(pt(q=abs(t4), df=df1, lower.tail=TRUE)),3)
p5<-2*round(1-(pt(q=abs(t5), df=df1, lower.tail=TRUE)),3)
p6<-2*round(1-(pt(q=abs(t6), df=df1, lower.tail=TRUE)),3)
p7<-2*round(1-(pt(q=abs(t7), df=df1, lower.tail=TRUE)),3)
p8<-2*round(1-(pt(q=abs(t8), df=df1, lower.tail=TRUE)),3)
p9<-2*round(1-(pt(q=abs(t9), df=df1, lower.tail=TRUE)),3)
t1<-round((t1),3)
t2<-round((t2),3)
t3<-round((t3),3)
t4<-round((t4),3)
t5<-round((t5),3)
t6<-round((t6),3)
t7<-round((t7),3)
t8<-round((t8),3)
t9<-round((t9),3)
message("Predictor 1: "," t = ", t1,", p = ", p1)
message("Predictor 2: "," t = ", t2,", p = ", p2)
message("Predictor 3: "," t = ", t3,", p = ", p3)
message("Predictor 4: "," t = ", t4,", p = ", p4)
message("Predictor 5: "," t = ", t5,", p = ", p5)
message("Predictor 6: "," t = ", t6,", p = ", p6)
message("Predictor 7: "," t = ", t7,", p = ", p7)
message("Predictor 8: "," t = ", t8,", p = ", p8)
message("Predictor 9: "," t = ", t9,", p = ", p9)
}
if ((pred =="10") && (comps=="abs")){
b1_1<-(model1$coefficients)[2,4]
b2_1<-(model1$coefficients)[3,4]
b3_1<-(model1$coefficients)[4,4]
b4_1<-(model1$coefficients)[5,4]
b5_1<-(model1$coefficients)[6,4]
b6_1<-(model1$coefficients)[7,4]
b7_1<-(model1$coefficients)[8,4]
b8_1<-(model1$coefficients)[9,4]
b9_1<-(model1$coefficients)[10,4]
b10_1<-(model1$coefficients)[11,4]
b1_2<-(model2$coefficients)[2,4]
b2_2<-(model2$coefficients)[3,4]
b3_2<-(model2$coefficients)[4,4]
b4_2<-(model2$coefficients)[5,4]
b5_2<-(model2$coefficients)[6,4]
b6_2<-(model2$coefficients)[7,4]
b7_2<-(model2$coefficients)[8,4]
b8_2<-(model2$coefficients)[9,4]
b9_2<-(model2$coefficients)[10,4]
b10_2<-(model2$coefficients)[11,4]
seb1_1<-(model1$coefficients)[2,2]
seb2_1<-(model1$coefficients)[3,2]
seb3_1<-(model1$coefficients)[4,2]
seb4_1<-(model1$coefficients)[5,2]
seb5_1<-(model1$coefficients)[6,2]
seb6_1<-(model1$coefficients)[7,2]
seb7_1<-(model1$coefficients)[8,2]
seb8_1<-(model1$coefficients)[9,2]
seb9_1<-(model1$coefficients)[10,2]
seb10_1<-(model1$coefficients)[11,2]
seb1_2<-(model2$coefficients)[2,2]
seb2_2<-(model2$coefficients)[3,2]
seb3_2<-(model2$coefficients)[4,2]
seb4_2<-(model2$coefficients)[5,2]
seb5_2<-(model2$coefficients)[6,2]
seb6_2<-(model2$coefficients)[7,2]
seb7_2<-(model2$coefficients)[8,2]
seb8_2<-(model2$coefficients)[9,2]
seb9_2<-(model2$coefficients)[10,2]
seb10_2<-(model2$coefficients)[11,2]
sebb1<-((seb1_1^2)+(seb1_2^2))^.5
sebb2<-((seb2_1^2)+(seb2_2^2))^.5
sebb3<-((seb3_1^2)+(seb3_2^2))^.5
sebb4<-((seb4_1^2)+(seb4_2^2))^.5
sebb5<-((seb5_1^2)+(seb5_2^2))^.5
sebb6<-((seb6_1^2)+(seb6_2^2))^.5
sebb7<-((seb7_1^2)+(seb7_2^2))^.5
sebb8<-((seb8_1^2)+(seb8_2^2))^.5
sebb9<-((seb9_1^2)+(seb9_2^2))^.5
sebb10<-((seb10_1^2)+(seb10_2^2))^.5
t1<-abs(abs(b1_1)-abs(b1_2))/sebb1
t2<-abs(abs(b2_1)-abs(b2_2))/sebb2
t3<-abs(abs(b3_1)-abs(b3_2))/sebb3
t4<-abs(abs(b4_1)-abs(b4_2))/sebb4
t5<-abs(abs(b5_1)-abs(b5_2))/sebb5
t6<-abs(abs(b6_1)-abs(b6_2))/sebb6
t7<-abs(abs(b7_1)-abs(b7_2))/sebb7
t8<-abs(abs(b8_1)-abs(b8_2))/sebb8
t9<-abs(abs(b9_1)-abs(b9_2))/sebb9
t10<-abs(abs(b10_1)-abs(b10_2))/sebb10
df1<-model1$df[2]+model2$df[2]
p1<-2*round(1-(pt(q=abs(t1), df=df1, lower.tail=TRUE)),3)
p2<-2*round(1-(pt(q=abs(t2), df=df1, lower.tail=TRUE)),3)
p3<-2*round(1-(pt(q=abs(t3), df=df1, lower.tail=TRUE)),3)
p4<-2*round(1-(pt(q=abs(t4), df=df1, lower.tail=TRUE)),3)
p5<-2*round(1-(pt(q=abs(t5), df=df1, lower.tail=TRUE)),3)
p6<-2*round(1-(pt(q=abs(t6), df=df1, lower.tail=TRUE)),3)
p7<-2*round(1-(pt(q=abs(t7), df=df1, lower.tail=TRUE)),3)
p8<-2*round(1-(pt(q=abs(t8), df=df1, lower.tail=TRUE)),3)
p9<-2*round(1-(pt(q=abs(t9), df=df1, lower.tail=TRUE)),3)
p10<-2*round(1-(pt(q=abs(t10), df=df1, lower.tail=TRUE)),3)
t1<-round((t1),3)
t2<-round((t2),3)
t3<-round((t3),3)
t4<-round((t4),3)
t5<-round((t5),3)
t6<-round((t6),3)
t7<-round((t7),3)
t8<-round((t8),3)
t9<-round((t9),3)
t10<-round((t10),3)
message("Predictor 1: "," t = ", t1,", p = ", p1)
message("Predictor 2: "," t = ", t2,", p = ", p2)
message("Predictor 3: "," t = ", t3,", p = ", p3)
message("Predictor 4: "," t = ", t4,", p = ", p4)
message("Predictor 5: "," t = ", t5,", p = ", p5)
message("Predictor 6: "," t = ", t6,", p = ", p6)
message("Predictor 7: "," t = ", t7,", p = ", p7)
message("Predictor 8: "," t = ", t8,", p = ", p8)
message("Predictor 9: "," t = ", t9,", p = ", p9)
message("Predictor 10: "," t = ", t10,", p = ", p10)
}
if ((pred =="2") && (comps=="raw")){
b1_1<-(model1$coefficients)[2,4]
b2_1<-(model1$coefficients)[3,4]
b1_2<-(model2$coefficients)[2,4]
b2_2<-(model2$coefficients)[3,4]
seb1_1<-(model1$coefficients)[2,2]
seb2_1<-(model1$coefficients)[3,2]
seb1_2<-(model2$coefficients)[2,2]
seb2_2<-(model2$coefficients)[3,2]
sebb1<-((seb1_1^2)+(seb1_2^2))^.5
sebb2<-((seb2_1^2)+(seb2_2^2))^.5
t1<-((b1_1-b1_2))/sebb1
t2<-((b2_1-b2_2))/sebb2
df1<-model1$df[2]+model2$df[2]
df2<-model2$df[2]
p1<-2*round(1-(pt(q=abs(t1), df=df1, lower.tail=TRUE)),3)
p2<-2*round(1-(pt(q=abs(t2), df=df2, lower.tail=TRUE)),3)
t1<-round((t1),3)
t2<-round((t2),3)
message("Predictor 1: "," t = ", t1,", p = ", p1)
message("Predictor 2: "," t = ", t2,", p = ", p2)
}
if ((pred =="3") && (comps=="raw")){
b1_1<-(model1$coefficients)[2,4]
b2_1<-(model1$coefficients)[3,4]
b3_1<-(model1$coefficients)[4,4]
b1_2<-(model2$coefficients)[2,4]
b2_2<-(model2$coefficients)[3,4]
b3_2<-(model2$coefficients)[4,4]
seb1_1<-(model1$coefficients)[2,2]
seb2_1<-(model1$coefficients)[3,2]
seb3_1<-(model1$coefficients)[4,2]
seb1_2<-(model2$coefficients)[2,2]
seb2_2<-(model2$coefficients)[3,2]
seb3_2<-(model2$coefficients)[4,2]
sebb1<-((seb1_1^2)+(seb1_2^2))^.5
sebb2<-((seb2_1^2)+(seb2_2^2))^.5
sebb3<-((seb3_1^2)+(seb3_2^2))^.5
t1<-((b1_1-b1_2))/sebb1
t2<-((b2_1-b2_2))/sebb2
t3<-((b3_1-b3_2))/sebb3
df1<-model1$df[2]+model2$df[2]
p1<-2*round(1-(pt(q=abs(t1), df=df1, lower.tail=TRUE)),3)
p2<-2*round(1-(pt(q=abs(t2), df=df1, lower.tail=TRUE)),3)
p3<-2*round(1-(pt(q=abs(t3), df=df1, lower.tail=TRUE)),3)
t1<-round((t1),3)
t2<-round((t2),3)
t3<-round((t3),3)
message("Predictor 1: "," t = ", t1,", p = ", p1)
message("Predictor 2: "," t = ", t2,", p = ", p2)
message("Predictor 3: "," t = ", t3,", p = ", p3)
}
if ((pred =="4") && (comps=="raw")){
b1_1<-(model1$coefficients)[2,4]
b2_1<-(model1$coefficients)[3,4]
b3_1<-(model1$coefficients)[4,4]
b4_1<-(model1$coefficients)[5,4]
b1_2<-(model2$coefficients)[2,4]
b2_2<-(model2$coefficients)[3,4]
b3_2<-(model2$coefficients)[4,4]
b4_2<-(model2$coefficients)[5,4]
seb1_1<-(model1$coefficients)[2,2]
seb2_1<-(model1$coefficients)[3,2]
seb3_1<-(model1$coefficients)[4,2]
seb4_1<-(model1$coefficients)[5,2]
seb1_2<-(model2$coefficients)[2,2]
seb2_2<-(model2$coefficients)[3,2]
seb3_2<-(model2$coefficients)[4,2]
seb4_2<-(model2$coefficients)[5,2]
sebb1<-((seb1_1^2)+(seb1_2^2))^.5
sebb2<-((seb2_1^2)+(seb2_2^2))^.5
sebb3<-((seb3_1^2)+(seb3_2^2))^.5
sebb4<-((seb4_1^2)+(seb4_2^2))^.5
t1<-((b1_1-b1_2))/sebb1
t2<-((b2_1-b2_2))/sebb2
t3<-((b3_1-b3_2))/sebb3
t4<-((b4_1-b4_2))/sebb4
df1<-model1$df[2]+model2$df[2]
p1<-2*round(1-(pt(q=abs(t1), df=df1, lower.tail=TRUE)),3)
p2<-2*round(1-(pt(q=abs(t2), df=df1, lower.tail=TRUE)),3)
p3<-2*round(1-(pt(q=abs(t3), df=df1, lower.tail=TRUE)),3)
p4<-2*round(1-(pt(q=abs(t4), df=df1, lower.tail=TRUE)),3)
t1<-round((t1),3)
t2<-round((t2),3)
t3<-round((t3),3)
t4<-round((t4),3)
message("Predictor 1: "," t = ", t1,", p = ", p1)
message("Predictor 2: "," t = ", t2,", p = ", p2)
message("Predictor 3: "," t = ", t3,", p = ", p3)
message("Predictor 4: "," t = ", t4,", p = ", p4)
}
if ((pred =="5") && (comps=="raw")){
b1_1<-(model1$coefficients)[2,4]
b2_1<-(model1$coefficients)[3,4]
b3_1<-(model1$coefficients)[4,4]
b4_1<-(model1$coefficients)[5,4]
b5_1<-(model1$coefficients)[6,4]
b1_2<-(model2$coefficients)[2,4]
b2_2<-(model2$coefficients)[3,4]
b3_2<-(model2$coefficients)[4,4]
b4_2<-(model2$coefficients)[5,4]
b5_2<-(model2$coefficients)[6,4]
seb1_1<-(model1$coefficients)[2,2]
seb2_1<-(model1$coefficients)[3,2]
seb3_1<-(model1$coefficients)[4,2]
seb4_1<-(model1$coefficients)[5,2]
seb5_1<-(model1$coefficients)[6,2]
seb1_2<-(model2$coefficients)[2,2]
seb2_2<-(model2$coefficients)[3,2]
seb3_2<-(model2$coefficients)[4,2]
seb4_2<-(model2$coefficients)[5,2]
seb5_2<-(model2$coefficients)[6,2]
sebb1<-((seb1_1^2)+(seb1_2^2))^.5
sebb2<-((seb2_1^2)+(seb2_2^2))^.5
sebb3<-((seb3_1^2)+(seb3_2^2))^.5
sebb4<-((seb4_1^2)+(seb4_2^2))^.5
sebb5<-((seb5_1^2)+(seb5_2^2))^.5
t1<-((b1_1-b1_2))/sebb1
t2<-((b2_1-b2_2))/sebb2
t3<-((b3_1-b3_2))/sebb3
t4<-((b4_1-b4_2))/sebb4
t5<-((b5_1-b5_2))/sebb5
df1<-model1$df[2]+model2$df[2]
p1<-2*round(1-(pt(q=abs(t1), df=df1, lower.tail=TRUE)),3)
p2<-2*round(1-(pt(q=abs(t2), df=df1, lower.tail=TRUE)),3)
p3<-2*round(1-(pt(q=abs(t3), df=df1, lower.tail=TRUE)),3)
p4<-2*round(1-(pt(q=abs(t4), df=df1, lower.tail=TRUE)),3)
p5<-2*round(1-(pt(q=abs(t5), df=df1, lower.tail=TRUE)),3)
t1<-round((t1),3)
t2<-round((t2),3)
t3<-round((t3),3)
t4<-round((t4),3)
t5<-round((t5),3)
message("Predictor 1: "," t = ", t1,", p = ", p1)
message("Predictor 2: "," t = ", t2,", p = ", p2)
message("Predictor 3: "," t = ", t3,", p = ", p3)
message("Predictor 4: "," t = ", t4,", p = ", p4)
message("Predictor 5: "," t = ", t5,", p = ", p5)
}
if ((pred =="6") && (comps=="raw")){
b1_1<-(model1$coefficients)[2,4]
b2_1<-(model1$coefficients)[3,4]
b3_1<-(model1$coefficients)[4,4]
b4_1<-(model1$coefficients)[5,4]
b5_1<-(model1$coefficients)[6,4]
b6_1<-(model1$coefficients)[7,4]
b1_2<-(model2$coefficients)[2,4]
b2_2<-(model2$coefficients)[3,4]
b3_2<-(model2$coefficients)[4,4]
b4_2<-(model2$coefficients)[5,4]
b5_2<-(model2$coefficients)[6,4]
b6_2<-(model2$coefficients)[7,4]
seb1_1<-(model1$coefficients)[2,2]
seb2_1<-(model1$coefficients)[3,2]
seb3_1<-(model1$coefficients)[4,2]
seb4_1<-(model1$coefficients)[5,2]
seb5_1<-(model1$coefficients)[6,2]
seb6_1<-(model1$coefficients)[7,2]
seb1_2<-(model2$coefficients)[2,2]
seb2_2<-(model2$coefficients)[3,2]
seb3_2<-(model2$coefficients)[4,2]
seb4_2<-(model2$coefficients)[5,2]
seb5_2<-(model2$coefficients)[6,2]
seb6_2<-(model2$coefficients)[7,2]
sebb1<-((seb1_1^2)+(seb1_2^2))^.5
sebb2<-((seb2_1^2)+(seb2_2^2))^.5
sebb3<-((seb3_1^2)+(seb3_2^2))^.5
sebb4<-((seb4_1^2)+(seb4_2^2))^.5
sebb5<-((seb5_1^2)+(seb5_2^2))^.5
sebb6<-((seb6_1^2)+(seb6_2^2))^.5
t1<-((b1_1-b1_2))/sebb1
t2<-((b2_1-b2_2))/sebb2
t3<-((b3_1-b3_2))/sebb3
t4<-((b4_1-b4_2))/sebb4
t5<-((b5_1-b5_2))/sebb5
t6<-((b6_1-b6_2))/sebb6
df1<-model1$df[2]+model2$df[2]
p1<-2*round(1-(pt(q=abs(t1), df=df1, lower.tail=TRUE)),3)
p2<-2*round(1-(pt(q=abs(t2), df=df1, lower.tail=TRUE)),3)
p3<-2*round(1-(pt(q=abs(t3), df=df1, lower.tail=TRUE)),3)
p4<-2*round(1-(pt(q=abs(t4), df=df1, lower.tail=TRUE)),3)
p5<-2*round(1-(pt(q=abs(t5), df=df1, lower.tail=TRUE)),3)
p6<-2*round(1-(pt(q=abs(t6), df=df1, lower.tail=TRUE)),3)
t1<-round((t1),3)
t2<-round((t2),3)
t3<-round((t3),3)
t4<-round((t4),3)
t5<-round((t5),3)
t6<-round((t6),3)
message("Predictor 1: "," t = ", t1,", p = ", p1)
message("Predictor 2: "," t = ", t2,", p = ", p2)
message("Predictor 3: "," t = ", t3,", p = ", p3)
message("Predictor 4: "," t = ", t4,", p = ", p4)
message("Predictor 5: "," t = ", t5,", p = ", p5)
message("Predictor 6: "," t = ", t6,", p = ", p6)
}
if ((pred =="7") && (comps=="raw")){
b1_1<-(model1$coefficients)[2,4]
b2_1<-(model1$coefficients)[3,4]
b3_1<-(model1$coefficients)[4,4]
b4_1<-(model1$coefficients)[5,4]
b5_1<-(model1$coefficients)[6,4]
b6_1<-(model1$coefficients)[7,4]
b7_1<-(model1$coefficients)[8,4]
b1_2<-(model2$coefficients)[2,4]
b2_2<-(model2$coefficients)[3,4]
b3_2<-(model2$coefficients)[4,4]
b4_2<-(model2$coefficients)[5,4]
b5_2<-(model2$coefficients)[6,4]
b6_2<-(model2$coefficients)[7,4]
b7_2<-(model2$coefficients)[8,4]
seb1_1<-(model1$coefficients)[2,2]
seb2_1<-(model1$coefficients)[3,2]
seb3_1<-(model1$coefficients)[4,2]
seb4_1<-(model1$coefficients)[5,2]
seb5_1<-(model1$coefficients)[6,2]
seb6_1<-(model1$coefficients)[7,2]
seb7_1<-(model1$coefficients)[8,2]
seb1_2<-(model2$coefficients)[2,2]
seb2_2<-(model2$coefficients)[3,2]
seb3_2<-(model2$coefficients)[4,2]
seb4_2<-(model2$coefficients)[5,2]
seb5_2<-(model2$coefficients)[6,2]
seb6_2<-(model2$coefficients)[7,2]
seb7_2<-(model2$coefficients)[8,2]
sebb1<-((seb1_1^2)+(seb1_2^2))^.5
sebb2<-((seb2_1^2)+(seb2_2^2))^.5
sebb3<-((seb3_1^2)+(seb3_2^2))^.5
sebb4<-((seb4_1^2)+(seb4_2^2))^.5
sebb5<-((seb5_1^2)+(seb5_2^2))^.5
sebb6<-((seb6_1^2)+(seb6_2^2))^.5
sebb7<-((seb7_1^2)+(seb7_2^2))^.5
t1<-((b1_1-b1_2))/sebb1
t2<-((b2_1-b2_2))/sebb2
t3<-((b3_1-b3_2))/sebb3
t4<-((b4_1-b4_2))/sebb4
t5<-((b5_1-b5_2))/sebb5
t6<-((b6_1-b6_2))/sebb6
t7<-((b7_1-b7_2))/sebb7
df1<-model1$df[2]+model2$df[2]
p1<-2*round(1-(pt(q=abs(t1), df=df1, lower.tail=TRUE)),3)
p2<-2*round(1-(pt(q=abs(t2), df=df1, lower.tail=TRUE)),3)
p3<-2*round(1-(pt(q=abs(t3), df=df1, lower.tail=TRUE)),3)
p4<-2*round(1-(pt(q=abs(t4), df=df1, lower.tail=TRUE)),3)
p5<-2*round(1-(pt(q=abs(t5), df=df1, lower.tail=TRUE)),3)
p6<-2*round(1-(pt(q=abs(t6), df=df1, lower.tail=TRUE)),3)
p7<-2*round(1-(pt(q=abs(t7), df=df1, lower.tail=TRUE)),3)
t1<-round((t1),3)
t2<-round((t2),3)
t3<-round((t3),3)
t4<-round((t4),3)
t5<-round((t5),3)
t6<-round((t6),3)
t7<-round((t7),3)
message("Predictor 1: "," t = ", t1,", p = ", p1)
message("Predictor 2: "," t = ", t2,", p = ", p2)
message("Predictor 3: "," t = ", t3,", p = ", p3)
message("Predictor 4: "," t = ", t4,", p = ", p4)
message("Predictor 5: "," t = ", t5,", p = ", p5)
message("Predictor 6: "," t = ", t6,", p = ", p6)
message("Predictor 7: "," t = ", t7,", p = ", p7)
}
if ((pred =="8") && (comps=="raw")){
b1_1<-(model1$coefficients)[2,4]
b2_1<-(model1$coefficients)[3,4]
b3_1<-(model1$coefficients)[4,4]
b4_1<-(model1$coefficients)[5,4]
b5_1<-(model1$coefficients)[6,4]
b6_1<-(model1$coefficients)[7,4]
b7_1<-(model1$coefficients)[8,4]
b8_1<-(model1$coefficients)[9,4]
b1_2<-(model2$coefficients)[2,4]
b2_2<-(model2$coefficients)[3,4]
b3_2<-(model2$coefficients)[4,4]
b4_2<-(model2$coefficients)[5,4]
b5_2<-(model2$coefficients)[6,4]
b6_2<-(model2$coefficients)[7,4]
b7_2<-(model2$coefficients)[8,4]
b8_2<-(model2$coefficients)[9,4]
seb1_1<-(model1$coefficients)[2,2]
seb2_1<-(model1$coefficients)[3,2]
seb3_1<-(model1$coefficients)[4,2]
seb4_1<-(model1$coefficients)[5,2]
seb5_1<-(model1$coefficients)[6,2]
seb6_1<-(model1$coefficients)[7,2]
seb7_1<-(model1$coefficients)[8,2]
seb8_1<-(model1$coefficients)[9,2]
seb1_2<-(model2$coefficients)[2,2]
seb2_2<-(model2$coefficients)[3,2]
seb3_2<-(model2$coefficients)[4,2]
seb4_2<-(model2$coefficients)[5,2]
seb5_2<-(model2$coefficients)[6,2]
seb6_2<-(model2$coefficients)[7,2]
seb7_2<-(model2$coefficients)[8,2]
seb8_2<-(model2$coefficients)[9,2]
sebb1<-((seb1_1^2)+(seb1_2^2))^.5
sebb2<-((seb2_1^2)+(seb2_2^2))^.5
sebb3<-((seb3_1^2)+(seb3_2^2))^.5
sebb4<-((seb4_1^2)+(seb4_2^2))^.5
sebb5<-((seb5_1^2)+(seb5_2^2))^.5
sebb6<-((seb6_1^2)+(seb6_2^2))^.5
sebb7<-((seb7_1^2)+(seb7_2^2))^.5
sebb8<-((seb8_1^2)+(seb8_2^2))^.5
t1<-((b1_1-b1_2))/sebb1
t2<-((b2_1-b2_2))/sebb2
t3<-((b3_1-b3_2))/sebb3
t4<-((b4_1-b4_2))/sebb4
t5<-((b5_1-b5_2))/sebb5
t6<-((b6_1-b6_2))/sebb6
t7<-((b7_1-b7_2))/sebb7
t8<-((b8_1-b8_2))/sebb8
df1<-model1$df[2]+model2$df[2]
p1<-2*round(1-(pt(q=abs(t1), df=df1, lower.tail=TRUE)),3)
p2<-2*round(1-(pt(q=abs(t2), df=df1, lower.tail=TRUE)),3)
p3<-2*round(1-(pt(q=abs(t3), df=df1, lower.tail=TRUE)),3)
p4<-2*round(1-(pt(q=abs(t4), df=df1, lower.tail=TRUE)),3)
p5<-2*round(1-(pt(q=abs(t5), df=df1, lower.tail=TRUE)),3)
p6<-2*round(1-(pt(q=abs(t6), df=df1, lower.tail=TRUE)),3)
p7<-2*round(1-(pt(q=abs(t7), df=df1, lower.tail=TRUE)),3)
p8<-2*round(1-(pt(q=abs(t8), df=df1, lower.tail=TRUE)),3)
t1<-round((t1),3)
t2<-round((t2),3)
t3<-round((t3),3)
t4<-round((t4),3)
t5<-round((t5),3)
t6<-round((t6),3)
t7<-round((t7),3)
t8<-round((t8),3)
message("Predictor 1: "," t = ", t1,", p = ", p1)
message("Predictor 2: "," t = ", t2,", p = ", p2)
message("Predictor 3: "," t = ", t3,", p = ", p3)
message("Predictor 4: "," t = ", t4,", p = ", p4)
message("Predictor 5: "," t = ", t5,", p = ", p5)
message("Predictor 6: "," t = ", t6,", p = ", p6)
message("Predictor 7: "," t = ", t7,", p = ", p7)
message("Predictor 8: "," t = ", t8,", p = ", p8)
}
if ((pred =="9") && (comps=="raw")){
b1_1<-(model1$coefficients)[2,4]
b2_1<-(model1$coefficients)[3,4]
b3_1<-(model1$coefficients)[4,4]
b4_1<-(model1$coefficients)[5,4]
b5_1<-(model1$coefficients)[6,4]
b6_1<-(model1$coefficients)[7,4]
b7_1<-(model1$coefficients)[8,4]
b8_1<-(model1$coefficients)[9,4]
b9_1<-(model1$coefficients)[10,4]
b1_2<-(model2$coefficients)[2,4]
b2_2<-(model2$coefficients)[3,4]
b3_2<-(model2$coefficients)[4,4]
b4_2<-(model2$coefficients)[5,4]
b5_2<-(model2$coefficients)[6,4]
b6_2<-(model2$coefficients)[7,4]
b7_2<-(model2$coefficients)[8,4]
b8_2<-(model2$coefficients)[9,4]
b9_2<-(model2$coefficients)[10,4]
seb1_1<-(model1$coefficients)[2,2]
seb2_1<-(model1$coefficients)[3,2]
seb3_1<-(model1$coefficients)[4,2]
seb4_1<-(model1$coefficients)[5,2]
seb5_1<-(model1$coefficients)[6,2]
seb6_1<-(model1$coefficients)[7,2]
seb7_1<-(model1$coefficients)[8,2]
seb8_1<-(model1$coefficients)[9,2]
seb9_1<-(model1$coefficients)[10,2]
seb1_2<-(model2$coefficients)[2,2]
seb2_2<-(model2$coefficients)[3,2]
seb3_2<-(model2$coefficients)[4,2]
seb4_2<-(model2$coefficients)[5,2]
seb5_2<-(model2$coefficients)[6,2]
seb6_2<-(model2$coefficients)[7,2]
seb7_2<-(model2$coefficients)[8,2]
seb8_2<-(model2$coefficients)[9,2]
seb9_2<-(model2$coefficients)[10,2]
sebb1<-((seb1_1^2)+(seb1_2^2))^.5
sebb2<-((seb2_1^2)+(seb2_2^2))^.5
sebb3<-((seb3_1^2)+(seb3_2^2))^.5
sebb4<-((seb4_1^2)+(seb4_2^2))^.5
sebb5<-((seb5_1^2)+(seb5_2^2))^.5
sebb6<-((seb6_1^2)+(seb6_2^2))^.5
sebb7<-((seb7_1^2)+(seb7_2^2))^.5
sebb8<-((seb8_1^2)+(seb8_2^2))^.5
sebb9<-((seb9_1^2)+(seb9_2^2))^.5
t1<-((b1_1-b1_2))/sebb1
t2<-((b2_1-b2_2))/sebb2
t3<-((b3_1-b3_2))/sebb3
t4<-((b4_1-b4_2))/sebb4
t5<-((b5_1-b5_2))/sebb5
t6<-((b6_1-b6_2))/sebb6
t7<-((b7_1-b7_2))/sebb7
t8<-((b8_1-b8_2))/sebb8
t9<-((b9_1-b9_2))/sebb9
df1<-model1$df[2]+model2$df[2]
p1<-2*round(1-(pt(q=abs(t1), df=df1, lower.tail=TRUE)),3)
p2<-2*round(1-(pt(q=abs(t2), df=df1, lower.tail=TRUE)),3)
p3<-2*round(1-(pt(q=abs(t3), df=df1, lower.tail=TRUE)),3)
p4<-2*round(1-(pt(q=abs(t4), df=df1, lower.tail=TRUE)),3)
p5<-2*round(1-(pt(q=abs(t5), df=df1, lower.tail=TRUE)),3)
p6<-2*round(1-(pt(q=abs(t6), df=df1, lower.tail=TRUE)),3)
p7<-2*round(1-(pt(q=abs(t7), df=df1, lower.tail=TRUE)),3)
p8<-2*round(1-(pt(q=abs(t8), df=df1, lower.tail=TRUE)),3)
p9<-2*round(1-(pt(q=abs(t9), df=df1, lower.tail=TRUE)),3)
t1<-round((t1),3)
t2<-round((t2),3)
t3<-round((t3),3)
t4<-round((t4),3)
t5<-round((t5),3)
t6<-round((t6),3)
t7<-round((t7),3)
t8<-round((t8),3)
t9<-round((t9),3)
message("Predictor 1: "," t = ", t1,", p = ", p1)
message("Predictor 2: "," t = ", t2,", p = ", p2)
message("Predictor 3: "," t = ", t3,", p = ", p3)
message("Predictor 4: "," t = ", t4,", p = ", p4)
message("Predictor 5: "," t = ", t5,", p = ", p5)
message("Predictor 6: "," t = ", t6,", p = ", p6)
message("Predictor 7: "," t = ", t7,", p = ", p7)
message("Predictor 8: "," t = ", t8,", p = ", p8)
message("Predictor 9: "," t = ", t9,", p = ", p9)
}
if ((pred =="10") && (comps=="raw")){
b1_1<-(model1$coefficients)[2,4]
b2_1<-(model1$coefficients)[3,4]
b3_1<-(model1$coefficients)[4,4]
b4_1<-(model1$coefficients)[5,4]
b5_1<-(model1$coefficients)[6,4]
b6_1<-(model1$coefficients)[7,4]
b7_1<-(model1$coefficients)[8,4]
b8_1<-(model1$coefficients)[9,4]
b9_1<-(model1$coefficients)[10,4]
b10_1<-(model1$coefficients)[11,4]
b1_2<-(model2$coefficients)[2,4]
b2_2<-(model2$coefficients)[3,4]
b3_2<-(model2$coefficients)[4,4]
b4_2<-(model2$coefficients)[5,4]
b5_2<-(model2$coefficients)[6,4]
b6_2<-(model2$coefficients)[7,4]
b7_2<-(model2$coefficients)[8,4]
b8_2<-(model2$coefficients)[9,4]
b9_2<-(model2$coefficients)[10,4]
b10_2<-(model2$coefficients)[11,4]
seb1_1<-(model1$coefficients)[2,2]
seb2_1<-(model1$coefficients)[3,2]
seb3_1<-(model1$coefficients)[4,2]
seb4_1<-(model1$coefficients)[5,2]
seb5_1<-(model1$coefficients)[6,2]
seb6_1<-(model1$coefficients)[7,2]
seb7_1<-(model1$coefficients)[8,2]
seb8_1<-(model1$coefficients)[9,2]
seb9_1<-(model1$coefficients)[10,2]
seb10_1<-(model1$coefficients)[11,2]
seb1_2<-(model2$coefficients)[2,2]
seb2_2<-(model2$coefficients)[3,2]
seb3_2<-(model2$coefficients)[4,2]
seb4_2<-(model2$coefficients)[5,2]
seb5_2<-(model2$coefficients)[6,2]
seb6_2<-(model2$coefficients)[7,2]
seb7_2<-(model2$coefficients)[8,2]
seb8_2<-(model2$coefficients)[9,2]
seb9_2<-(model2$coefficients)[10,2]
seb10_2<-(model2$coefficients)[11,2]
sebb1<-((seb1_1^2)+(seb1_2^2))^.5
sebb2<-((seb2_1^2)+(seb2_2^2))^.5
sebb3<-((seb3_1^2)+(seb3_2^2))^.5
sebb4<-((seb4_1^2)+(seb4_2^2))^.5
sebb5<-((seb5_1^2)+(seb5_2^2))^.5
sebb6<-((seb6_1^2)+(seb6_2^2))^.5
sebb7<-((seb7_1^2)+(seb7_2^2))^.5
sebb8<-((seb8_1^2)+(seb8_2^2))^.5
sebb9<-((seb9_1^2)+(seb9_2^2))^.5
sebb10<-((seb10_1^2)+(seb10_2^2))^.5
t1<-((b1_1-b1_2))/sebb1
t2<-((b2_1-b2_2))/sebb2
t3<-((b3_1-b3_2))/sebb3
t4<-((b4_1-b4_2))/sebb4
t5<-((b5_1-b5_2))/sebb5
t6<-((b6_1-b6_2))/sebb6
t7<-((b7_1-b7_2))/sebb7
t8<-((b8_1-b8_2))/sebb8
t9<-((b9_1-b9_2))/sebb9
t10<-((b10_1-b10_2))/sebb10
df1<-model1$df[2]+model2$df[2]
p1<-2*round(1-(pt(q=abs(t1), df=df1, lower.tail=TRUE)),3)
p2<-2*round(1-(pt(q=abs(t2), df=df1, lower.tail=TRUE)),3)
p3<-2*round(1-(pt(q=abs(t3), df=df1, lower.tail=TRUE)),3)
p4<-2*round(1-(pt(q=abs(t4), df=df1, lower.tail=TRUE)),3)
p5<-2*round(1-(pt(q=abs(t5), df=df1, lower.tail=TRUE)),3)
p6<-2*round(1-(pt(q=abs(t6), df=df1, lower.tail=TRUE)),3)
p7<-2*round(1-(pt(q=abs(t7), df=df1, lower.tail=TRUE)),3)
p8<-2*round(1-(pt(q=abs(t8), df=df1, lower.tail=TRUE)),3)
p9<-2*round(1-(pt(q=abs(t9), df=df1, lower.tail=TRUE)),3)
p10<-2*round(1-(pt(q=abs(t10), df=df1, lower.tail=TRUE)),3)
t1<-round((t1),3)
t2<-round((t2),3)
t3<-round((t3),3)
t4<-round((t4),3)
t5<-round((t5),3)
t6<-round((t6),3)
t7<-round((t7),3)
t8<-round((t8),3)
t9<-round((t9),3)
t10<-round((t10),3)
message("Predictor 1: "," t = ", t1,", p = ", p1)
message("Predictor 2: "," t = ", t2,", p = ", p2)
message("Predictor 3: "," t = ", t3,", p = ", p3)
message("Predictor 4: "," t = ", t4,", p = ", p4)
message("Predictor 5: "," t = ", t5,", p = ", p5)
message("Predictor 6: "," t = ", t6,", p = ", p6)
message("Predictor 7: "," t = ", t7,", p = ", p7)
message("Predictor 8: "," t = ", t8,", p = ", p8)
message("Predictor 9: "," t = ", t9,", p = ", p9)
message("Predictor 10: "," t = ", t10,", p = ", p10)
}
}
chrisaberson/BetterReg documentation built on June 10, 2022, 10:03 p.m.
R Package Documentation
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Defines functions indbcomp
Documented in indbcomp
#'Comparing Independent Coefficients in Multiple Regression
#'@param model1 Summary of first model (see example for how to summarize)
#'@param model2 Summary of second model (see example for how to summarize)
#'@param comps Type of comparison. "abs" - absolute value of coefficient
#'@param pred Number of predictors
#'@examples
#'y_1<-rnorm(200); x1_1<-rnorm(200); x2_1<-rnorm(200)
#'y_2<-rnorm(200); x1_2<-rnorm(200);x2_2<-rnorm(200)
#'df1<-as.data.frame(cbind(y_1, x1_1,x2_1))
#'df2<-as.data.frame(cbind(y_2, x1_2,x2_2))
#'model1_2<-summary(lm(y_1~x1_1+x2_1, data=df1))
#'model2_2<-summary(lm(y_2~x1_2+x2_2, data=df2))
#'indbcomp(model1 = model1_2, model2 = model2_2, comps="abs", pred=2)
#'@return Comparing Independent Coefficients in Multiple Regression
#'@export
#'
indbcomp<-function(model1=NULL, model2=NULL, comps="abs", pred=NULL)
{
if ((pred =="2") && (comps=="abs")){
b1_1<-(model1$coefficients)[2,4]
b2_1<-(model1$coefficients)[3,4]
b1_2<-(model2$coefficients)[2,4]
b2_2<-(model2$coefficients)[3,4]
seb1_1<-model1$coefficients[2,2]
seb2_1<-model1$coefficients[3,2]
seb1_2<-model2$coefficients[2,2]
seb2_2<-model2$coefficients[3,2]
sebb1<-((seb1_1^2)+(seb2_1^2))^.5
sebb2<-((seb1_2^2)+(seb2_2^2))^.5
t1<-abs(abs(b1_1)-abs(b1_2))/sebb1
t2<-abs(abs(b2_1)-abs(b2_2))/sebb2
df1<-model1$df[2]+model2$df[2]
df2<-model2$df[2]
p1<-2*round(1-(pt(q=abs(t1), df=df1, lower.tail=TRUE)),3)
p2<-2*round(1-(pt(q=abs(t2), df=df2, lower.tail=TRUE)),3)
t1<-round((t1),3)
t2<-round((t2),3)
message("Predictor 1: "," t = ", t1,", p = ", p1)
message("Predictor 2: "," t = ", t2,", p = ", p2)
}
if ((pred =="3") && (comps=="abs")){
b1_1<-(model1$coefficients)[2,4]
b2_1<-(model1$coefficients)[3,4]
b3_1<-(model1$coefficients)[4,4]
b1_2<-(model2$coefficients)[2,4]
b2_2<-(model2$coefficients)[3,4]
b3_2<-(model2$coefficients)[4,4]
seb1_1<-model1$coefficients[2,2]
seb2_1<-model1$coefficients[3,2]
seb3_1<-model1$coefficients[4,2]
seb1_2<-model2$coefficients[2,2]
seb2_2<-model2$coefficients[3,2]
seb3_2<-model2$coefficients[4,2]
sebb1<-((seb1_1^2)+(seb1_2^2))^.5
sebb2<-((seb2_1^2)+(seb2_2^2))^.5
sebb3<-((seb3_1^2)+(seb3_2^2))^.5
t1<-abs(abs(b1_1)-abs(b1_2))/sebb1
t2<-abs(abs(b2_1)-abs(b2_2))/sebb2
t3<-abs(abs(b3_1)-abs(b3_2))/sebb3
df1<-model1$df[2]+model2$df[2]
p1<-2*round(1-(pt(q=abs(t1), df=df1, lower.tail=TRUE)),3)
p2<-2*round(1-(pt(q=abs(t2), df=df1, lower.tail=TRUE)),3)
p3<-2*round(1-(pt(q=abs(t3), df=df1, lower.tail=TRUE)),3)
t1<-round((t1),3)
t2<-round((t2),3)
t3<-round((t3),3)
message("Predictor 1: "," t = ", t1,", p = ", p1)
message("Predictor 2: "," t = ", t2,", p = ", p2)
message("Predictor 3: "," t = ", t3,", p = ", p3)
}
if ((pred =="4") && (comps=="abs")){
b1_1<-(model1$coefficients)[2,4]
b2_1<-(model1$coefficients)[3,4]
b3_1<-(model1$coefficients)[4,4]
b4_1<-(model1$coefficients)[5,4]
b1_2<-(model2$coefficients)[2,4]
b2_2<-(model2$coefficients)[3,4]
b3_2<-(model2$coefficients)[4,4]
b4_2<-(model2$coefficients)[5,4]
seb1_1<-model1$coefficients[2,2]
seb2_1<-model1$coefficients[3,2]
seb3_1<-model1$coefficients[4,2]
seb4_1<-model1$coefficients[5,2]
seb1_2<-model2$coefficients[2,2]
seb2_2<-model2$coefficients[3,2]
seb3_2<-model2$coefficients[4,2]
seb4_2<-model2$coefficients[5,2]
sebb1<-((seb1_1^2)+(seb1_2^2))^.5
sebb2<-((seb2_1^2)+(seb2_2^2))^.5
sebb3<-((seb3_1^2)+(seb3_2^2))^.5
sebb4<-((seb4_1^2)+(seb4_2^2))^.5
t1<-abs(abs(b1_1)-abs(b1_2))/sebb1
t2<-abs(abs(b2_1)-abs(b2_2))/sebb2
t3<-abs(abs(b3_1)-abs(b3_2))/sebb3
t4<-abs(abs(b4_1)-abs(b4_2))/sebb4
df1<-model1$df[2]+model2$df[2]
p1<-2*round(1-(pt(q=abs(t1), df=df1, lower.tail=TRUE)),3)
p2<-2*round(1-(pt(q=abs(t2), df=df1, lower.tail=TRUE)),3)
p3<-2*round(1-(pt(q=abs(t3), df=df1, lower.tail=TRUE)),3)
p4<-2*round(1-(pt(q=abs(t4), df=df1, lower.tail=TRUE)),3)
t1<-round((t1),3)
t2<-round((t2),3)
t3<-round((t3),3)
t4<-round((t4),3)
message("Predictor 1: "," t = ", t1,", p = ", p1)
message("Predictor 2: "," t = ", t2,", p = ", p2)
message("Predictor 3: "," t = ", t3,", p = ", p3)
message("Predictor 4: "," t = ", t4,", p = ", p4)
}
if ((pred =="5") && (comps=="abs")){
b1_1<-(model1$coefficients)[2,4]
b2_1<-(model1$coefficients)[3,4]
b3_1<-(model1$coefficients)[4,4]
b4_1<-(model1$coefficients)[5,4]
b5_1<-(model1$coefficients)[6,4]
b1_2<-(model2$coefficients)[2,4]
b2_2<-(model2$coefficients)[3,4]
b3_2<-(model2$coefficients)[4,4]
b4_2<-(model2$coefficients)[5,4]
b5_2<-(model2$coefficients)[6,4]
seb1_1<-model1$coefficients[2,2]
seb2_1<-model1$coefficients[3,2]
seb3_1<-model1$coefficients[4,2]
seb4_1<-model1$coefficients[5,2]
seb5_1<-model1$coefficients[6,2]
seb1_2<-model2$coefficients[2,2]
seb2_2<-model2$coefficients[3,2]
seb3_2<-model2$coefficients[4,2]
seb4_2<-model2$coefficients[5,2]
seb5_2<-model2$coefficients[6,2]
sebb1<-((seb1_1^2)+(seb1_2^2))^.5
sebb2<-((seb2_1^2)+(seb2_2^2))^.5
sebb3<-((seb3_1^2)+(seb3_2^2))^.5
sebb4<-((seb4_1^2)+(seb4_2^2))^.5
sebb5<-((seb5_1^2)+(seb5_2^2))^.5
t1<-abs(abs(b1_1)-abs(b1_2))/sebb1
t2<-abs(abs(b2_1)-abs(b2_2))/sebb2
t3<-abs(abs(b3_1)-abs(b3_2))/sebb3
t4<-abs(abs(b4_1)-abs(b4_2))/sebb4
t5<-abs(abs(b5_1)-abs(b5_2))/sebb5
df1<-model1$df[2]+model2$df[2]
p1<-2*round(1-(pt(q=abs(t1), df=df1, lower.tail=TRUE)),3)
p2<-2*round(1-(pt(q=abs(t2), df=df1, lower.tail=TRUE)),3)
p3<-2*round(1-(pt(q=abs(t3), df=df1, lower.tail=TRUE)),3)
p4<-2*round(1-(pt(q=abs(t4), df=df1, lower.tail=TRUE)),3)
p5<-2*round(1-(pt(q=abs(t5), df=df1, lower.tail=TRUE)),3)
t1<-round((t1),3)
t2<-round((t2),3)
t3<-round((t3),3)
t4<-round((t4),3)
t5<-round((t5),3)
message("Predictor 1: "," t = ", t1,", p = ", p1)
message("Predictor 2: "," t = ", t2,", p = ", p2)
message("Predictor 3: "," t = ", t3,", p = ", p3)
message("Predictor 4: "," t = ", t4,", p = ", p4)
message("Predictor 5: "," t = ", t5,", p = ", p5)
}
if ((pred =="6") && (comps=="abs")){
b1_1<-(model1$coefficients)[2,4]
b2_1<-(model1$coefficients)[3,4]
b3_1<-(model1$coefficients)[4,4]
b4_1<-(model1$coefficients)[5,4]
b5_1<-(model1$coefficients)[6,4]
b6_1<-(model1$coefficients)[7,4]
b1_2<-(model2$coefficients)[2,4]
b2_2<-(model2$coefficients)[3,4]
b3_2<-(model2$coefficients)[4,4]
b4_2<-(model2$coefficients)[5,4]
b5_2<-(model2$coefficients)[6,4]
b6_2<-(model2$coefficients)[7,4]
seb1_1<-model1$coefficients[2,2]
seb2_1<-model1$coefficients[3,2]
seb3_1<-model1$coefficients[4,2]
seb4_1<-model1$coefficients[5,2]
seb5_1<-model1$coefficients[6,2]
seb6_1<-model1$coefficients[7,2]
seb1_2<-model2$coefficients[2,2]
seb2_2<-model2$coefficients[3,2]
seb3_2<-model2$coefficients[4,2]
seb4_2<-model2$coefficients[5,2]
seb5_2<-model2$coefficients[6,2]
seb6_2<-model2$coefficients[7,2]
sebb1<-((seb1_1^2)+(seb1_2^2))^.5
sebb2<-((seb2_1^2)+(seb2_2^2))^.5
sebb3<-((seb3_1^2)+(seb3_2^2))^.5
sebb4<-((seb4_1^2)+(seb4_2^2))^.5
sebb5<-((seb5_1^2)+(seb5_2^2))^.5
sebb6<-((seb6_1^2)+(seb6_2^2))^.5
t1<-abs(abs(b1_1)-abs(b1_2))/sebb1
t2<-abs(abs(b2_1)-abs(b2_2))/sebb2
t3<-abs(abs(b3_1)-abs(b3_2))/sebb3
t4<-abs(abs(b4_1)-abs(b4_2))/sebb4
t5<-abs(abs(b5_1)-abs(b5_2))/sebb5
t6<-abs(abs(b6_1)-abs(b6_2))/sebb6
df1<-model1$df[2]+model2$df[2]
p1<-2*round(1-(pt(q=abs(t1), df=df1, lower.tail=TRUE)),3)
p2<-2*round(1-(pt(q=abs(t2), df=df1, lower.tail=TRUE)),3)
p3<-2*round(1-(pt(q=abs(t3), df=df1, lower.tail=TRUE)),3)
p4<-2*round(1-(pt(q=abs(t4), df=df1, lower.tail=TRUE)),3)
p5<-2*round(1-(pt(q=abs(t5), df=df1, lower.tail=TRUE)),3)
p6<-2*round(1-(pt(q=abs(t6), df=df1, lower.tail=TRUE)),3)
t1<-round((t1),3)
t2<-round((t2),3)
t3<-round((t3),3)
t4<-round((t4),3)
t5<-round((t5),3)
t6<-round((t6),3)
message("Predictor 1: "," t = ", t1,", p = ", p1)
message("Predictor 2: "," t = ", t2,", p = ", p2)
message("Predictor 3: "," t = ", t3,", p = ", p3)
message("Predictor 4: "," t = ", t4,", p = ", p4)
message("Predictor 5: "," t = ", t5,", p = ", p5)
message("Predictor 6: "," t = ", t6,", p = ", p6)
}
if ((pred =="7") && (comps=="abs")){
b1_1<-(model1$coefficients)[2,4]
b2_1<-(model1$coefficients)[3,4]
b3_1<-(model1$coefficients)[4,4]
b4_1<-(model1$coefficients)[5,4]
b5_1<-(model1$coefficients)[6,4]
b6_1<-(model1$coefficients)[7,4]
b7_1<-(model1$coefficients)[8,4]
b1_2<-(model2$coefficients)[2,4]
b2_2<-(model2$coefficients)[3,4]
b3_2<-(model2$coefficients)[4,4]
b4_2<-(model2$coefficients)[5,4]
b5_2<-(model2$coefficients)[6,4]
b6_2<-(model2$coefficients)[7,4]
b7_2<-(model2$coefficients)[8,4]
seb1_1<-model1$coefficients[2,2]
seb2_1<-model1$coefficients[3,2]
seb3_1<-model1$coefficients[4,2]
seb4_1<-model1$coefficients[5,2]
seb5_1<-model1$coefficients[6,2]
seb6_1<-model1$coefficients[7,2]
seb7_1<-model1$coefficients[8,2]
seb1_2<-model2$coefficients[2,2]
seb2_2<-model2$coefficients[3,2]
seb3_2<-model2$coefficients[4,2]
seb4_2<-model2$coefficients[5,2]
seb5_2<-model2$coefficients[6,2]
seb6_2<-model2$coefficients[7,2]
seb7_2<-model2$coefficients[8,2]
sebb1<-((seb1_1^2)+(seb1_2^2))^.5
sebb2<-((seb2_1^2)+(seb2_2^2))^.5
sebb3<-((seb3_1^2)+(seb3_2^2))^.5
sebb4<-((seb4_1^2)+(seb4_2^2))^.5
sebb5<-((seb5_1^2)+(seb5_2^2))^.5
sebb6<-((seb6_1^2)+(seb6_2^2))^.5
sebb7<-((seb7_1^2)+(seb7_2^2))^.5
t1<-abs(abs(b1_1)-abs(b1_2))/sebb1
t2<-abs(abs(b2_1)-abs(b2_2))/sebb2
t3<-abs(abs(b3_1)-abs(b3_2))/sebb3
t4<-abs(abs(b4_1)-abs(b4_2))/sebb4
t5<-abs(abs(b5_1)-abs(b5_2))/sebb5
t6<-abs(abs(b6_1)-abs(b6_2))/sebb6
t7<-abs(abs(b7_1)-abs(b7_2))/sebb7
df1<-model1$df[2]+model2$df[2]
p1<-2*round(1-(pt(q=abs(t1), df=df1, lower.tail=TRUE)),3)
p2<-2*round(1-(pt(q=abs(t2), df=df1, lower.tail=TRUE)),3)
p3<-2*round(1-(pt(q=abs(t3), df=df1, lower.tail=TRUE)),3)
p4<-2*round(1-(pt(q=abs(t4), df=df1, lower.tail=TRUE)),3)
p5<-2*round(1-(pt(q=abs(t5), df=df1, lower.tail=TRUE)),3)
p6<-2*round(1-(pt(q=abs(t6), df=df1, lower.tail=TRUE)),3)
p7<-2*round(1-(pt(q=abs(t7), df=df1, lower.tail=TRUE)),3)
t1<-round((t1),3)
t2<-round((t2),3)
t3<-round((t3),3)
t4<-round((t4),3)
t5<-round((t5),3)
t6<-round((t6),3)
t7<-round((t7),3)
message("Predictor 1: "," t = ", t1,", p = ", p1)
message("Predictor 2: "," t = ", t2,", p = ", p2)
message("Predictor 3: "," t = ", t3,", p = ", p3)
message("Predictor 4: "," t = ", t4,", p = ", p4)
message("Predictor 5: "," t = ", t5,", p = ", p5)
message("Predictor 6: "," t = ", t6,", p = ", p6)
message("Predictor 7: "," t = ", t7,", p = ", p7)
}
if ((pred =="8") && (comps=="abs")){
b1_1<-(model1$coefficients)[2,4]
b2_1<-(model1$coefficients)[3,4]
b3_1<-(model1$coefficients)[4,4]
b4_1<-(model1$coefficients)[5,4]
b5_1<-(model1$coefficients)[6,4]
b6_1<-(model1$coefficients)[7,4]
b7_1<-(model1$coefficients)[8,4]
b8_1<-(model1$coefficients)[9,4]
b1_2<-(model2$coefficients)[2,4]
b2_2<-(model2$coefficients)[3,4]
b3_2<-(model2$coefficients)[4,4]
b4_2<-(model2$coefficients)[5,4]
b5_2<-(model2$coefficients)[6,4]
b6_2<-(model2$coefficients)[7,4]
b7_2<-(model2$coefficients)[8,4]
b8_2<-(model2$coefficients)[9,4]
seb1_1<-model1$coefficients[2,2]
seb2_1<-model1$coefficients[3,2]
seb3_1<-model1$coefficients[4,2]
seb4_1<-model1$coefficients[5,2]
seb5_1<-model1$coefficients[6,2]
seb6_1<-model1$coefficients[7,2]
seb7_1<-model1$coefficients[8,2]
seb8_1<-model1$coefficients[9,2]
seb1_2<-model2$coefficients[2,2]
seb2_2<-model2$coefficients[3,2]
seb3_2<-model2$coefficients[4,2]
seb4_2<-model2$coefficients[5,2]
seb5_2<-model2$coefficients[6,2]
seb6_2<-model2$coefficients[7,2]
seb7_2<-model2$coefficients[8,2]
seb8_2<-model2$coefficients[9,2]
sebb1<-((seb1_1^2)+(seb1_2^2))^.5
sebb2<-((seb2_1^2)+(seb2_2^82))^.5
sebb3<-((seb3_1^2)+(seb3_2^2))^.5
sebb4<-((seb4_1^2)+(seb4_2^2))^.5
sebb5<-((seb5_1^2)+(seb5_2^2))^.5
sebb6<-((seb6_1^2)+(seb6_2^2))^.5
sebb7<-((seb7_1^2)+(seb7_2^2))^.5
sebb8<-((seb8_1^2)+(seb8_2^2))^.5
t1<-abs(abs(b1_1)-abs(b1_2))/sebb1
t2<-abs(abs(b2_1)-abs(b2_2))/sebb2
t3<-abs(abs(b3_1)-abs(b3_2))/sebb3
t4<-abs(abs(b4_1)-abs(b4_2))/sebb4
t5<-abs(abs(b5_1)-abs(b5_2))/sebb5
t6<-abs(abs(b6_1)-abs(b6_2))/sebb6
t7<-abs(abs(b7_1)-abs(b7_2))/sebb7
t8<-abs(abs(b8_1)-abs(b8_2))/sebb8
df1<-model1$df[2]+model2$df[2]
p1<-2*round(1-(pt(q=abs(t1), df=df1, lower.tail=TRUE)),3)
p2<-2*round(1-(pt(q=abs(t2), df=df1, lower.tail=TRUE)),3)
p3<-2*round(1-(pt(q=abs(t3), df=df1, lower.tail=TRUE)),3)
p4<-2*round(1-(pt(q=abs(t4), df=df1, lower.tail=TRUE)),3)
p5<-2*round(1-(pt(q=abs(t5), df=df1, lower.tail=TRUE)),3)
p6<-2*round(1-(pt(q=abs(t6), df=df1, lower.tail=TRUE)),3)
p7<-2*round(1-(pt(q=abs(t7), df=df1, lower.tail=TRUE)),3)
p8<-2*round(1-(pt(q=abs(t8), df=df1, lower.tail=TRUE)),3)
t1<-round((t1),3)
t2<-round((t2),3)
t3<-round((t3),3)
t4<-round((t4),3)
t5<-round((t5),3)
t6<-round((t6),3)
t7<-round((t7),3)
t8<-round((t8),3)
message("Predictor 1: "," t = ", t1,", p = ", p1)
message("Predictor 2: "," t = ", t2,", p = ", p2)
message("Predictor 3: "," t = ", t3,", p = ", p3)
message("Predictor 4: "," t = ", t4,", p = ", p4)
message("Predictor 5: "," t = ", t5,", p = ", p5)
message("Predictor 6: "," t = ", t6,", p = ", p6)
message("Predictor 7: "," t = ", t7,", p = ", p7)
message("Predictor 8: "," t = ", t8,", p = ", p8)
}
if ((pred =="9") && (comps=="abs")){
b1_1<-(model1$coefficients)[2,4]
b2_1<-(model1$coefficients)[3,4]
b3_1<-(model1$coefficients)[4,4]
b4_1<-(model1$coefficients)[5,4]
b5_1<-(model1$coefficients)[6,4]
b6_1<-(model1$coefficients)[7,4]
b7_1<-(model1$coefficients)[8,4]
b8_1<-(model1$coefficients)[9,4]
b9_1<-(model1$coefficients)[10,4]
b1_2<-(model2$coefficients)[2,4]
b2_2<-(model2$coefficients)[3,4]
b3_2<-(model2$coefficients)[4,4]
b4_2<-(model2$coefficients)[5,4]
b5_2<-(model2$coefficients)[6,4]
b6_2<-(model2$coefficients)[7,4]
b7_2<-(model2$coefficients)[8,4]
b8_2<-(model2$coefficients)[9,4]
b9_2<-(model2$coefficients)[10,4]
seb1_1<-model1$coefficients[2,2]
seb2_1<-model1$coefficients[3,2]
seb3_1<-model1$coefficients[4,2]
seb4_1<-model1$coefficients[5,2]
seb5_1<-model1$coefficients[6,2]
seb6_1<-model1$coefficients[7,2]
seb7_1<-model1$coefficients[8,2]
seb8_1<-model1$coefficients[9,2]
seb9_1<-model1$coefficients[10,2]
seb1_2<-model2$coefficients[2,2]
seb2_2<-model2$coefficients[3,2]
seb3_2<-model2$coefficients[4,2]
seb4_2<-model2$coefficients[5,2]
seb5_2<-model2$coefficients[6,2]
seb6_2<-model2$coefficients[7,2]
seb7_2<-model2$coefficients[8,2]
seb8_2<-model2$coefficients[9,2]
seb9_2<-(model2$coefficients)[10,2]
sebb1<-((seb1_1^2)+(seb1_2^2))^.5
sebb2<-((seb2_1^2)+(seb2_2^2))^.5
sebb3<-((seb3_1^2)+(seb3_2^2))^.5
sebb4<-((seb4_1^2)+(seb4_2^2))^.5
sebb5<-((seb5_1^2)+(seb5_2^2))^.5
sebb6<-((seb6_1^2)+(seb6_2^2))^.5
sebb7<-((seb7_1^2)+(seb7_2^2))^.5
sebb8<-((seb8_1^2)+(seb8_2^2))^.5
sebb9<-((seb9_1^2)+(seb9_2^2))^.5
t1<-abs(abs(b1_1)-abs(b1_2))/sebb1
t2<-abs(abs(b2_1)-abs(b2_2))/sebb2
t3<-abs(abs(b3_1)-abs(b3_2))/sebb3
t4<-abs(abs(b4_1)-abs(b4_2))/sebb4
t5<-abs(abs(b5_1)-abs(b5_2))/sebb5
t6<-abs(abs(b6_1)-abs(b6_2))/sebb6
t7<-abs(abs(b7_1)-abs(b7_2))/sebb7
t8<-abs(abs(b8_1)-abs(b8_2))/sebb8
t9<-abs(abs(b9_1)-abs(b9_2))/sebb9
df1<-model1$df[2]+model2$df[2]
p1<-2*round(1-(pt(q=abs(t1), df=df1, lower.tail=TRUE)),3)
p2<-2*round(1-(pt(q=abs(t2), df=df1, lower.tail=TRUE)),3)
p3<-2*round(1-(pt(q=abs(t3), df=df1, lower.tail=TRUE)),3)
p4<-2*round(1-(pt(q=abs(t4), df=df1, lower.tail=TRUE)),3)
p5<-2*round(1-(pt(q=abs(t5), df=df1, lower.tail=TRUE)),3)
p6<-2*round(1-(pt(q=abs(t6), df=df1, lower.tail=TRUE)),3)
p7<-2*round(1-(pt(q=abs(t7), df=df1, lower.tail=TRUE)),3)
p8<-2*round(1-(pt(q=abs(t8), df=df1, lower.tail=TRUE)),3)
p9<-2*round(1-(pt(q=abs(t9), df=df1, lower.tail=TRUE)),3)
t1<-round((t1),3)
t2<-round((t2),3)
t3<-round((t3),3)
t4<-round((t4),3)
t5<-round((t5),3)
t6<-round((t6),3)
t7<-round((t7),3)
t8<-round((t8),3)
t9<-round((t9),3)
message("Predictor 1: "," t = ", t1,", p = ", p1)
message("Predictor 2: "," t = ", t2,", p = ", p2)
message("Predictor 3: "," t = ", t3,", p = ", p3)
message("Predictor 4: "," t = ", t4,", p = ", p4)
message("Predictor 5: "," t = ", t5,", p = ", p5)
message("Predictor 6: "," t = ", t6,", p = ", p6)
message("Predictor 7: "," t = ", t7,", p = ", p7)
message("Predictor 8: "," t = ", t8,", p = ", p8)
message("Predictor 9: "," t = ", t9,", p = ", p9)
}
if ((pred =="10") && (comps=="abs")){
b1_1<-(model1$coefficients)[2,4]
b2_1<-(model1$coefficients)[3,4]
b3_1<-(model1$coefficients)[4,4]
b4_1<-(model1$coefficients)[5,4]
b5_1<-(model1$coefficients)[6,4]
b6_1<-(model1$coefficients)[7,4]
b7_1<-(model1$coefficients)[8,4]
b8_1<-(model1$coefficients)[9,4]
b9_1<-(model1$coefficients)[10,4]
b10_1<-(model1$coefficients)[11,4]
b1_2<-(model2$coefficients)[2,4]
b2_2<-(model2$coefficients)[3,4]
b3_2<-(model2$coefficients)[4,4]
b4_2<-(model2$coefficients)[5,4]
b5_2<-(model2$coefficients)[6,4]
b6_2<-(model2$coefficients)[7,4]
b7_2<-(model2$coefficients)[8,4]
b8_2<-(model2$coefficients)[9,4]
b9_2<-(model2$coefficients)[10,4]
b10_2<-(model2$coefficients)[11,4]
seb1_1<-(model1$coefficients)[2,2]
seb2_1<-(model1$coefficients)[3,2]
seb3_1<-(model1$coefficients)[4,2]
seb4_1<-(model1$coefficients)[5,2]
seb5_1<-(model1$coefficients)[6,2]
seb6_1<-(model1$coefficients)[7,2]
seb7_1<-(model1$coefficients)[8,2]
seb8_1<-(model1$coefficients)[9,2]
seb9_1<-(model1$coefficients)[10,2]
seb10_1<-(model1$coefficients)[11,2]
seb1_2<-(model2$coefficients)[2,2]
seb2_2<-(model2$coefficients)[3,2]
seb3_2<-(model2$coefficients)[4,2]
seb4_2<-(model2$coefficients)[5,2]
seb5_2<-(model2$coefficients)[6,2]
seb6_2<-(model2$coefficients)[7,2]
seb7_2<-(model2$coefficients)[8,2]
seb8_2<-(model2$coefficients)[9,2]
seb9_2<-(model2$coefficients)[10,2]
seb10_2<-(model2$coefficients)[11,2]
sebb1<-((seb1_1^2)+(seb1_2^2))^.5
sebb2<-((seb2_1^2)+(seb2_2^2))^.5
sebb3<-((seb3_1^2)+(seb3_2^2))^.5
sebb4<-((seb4_1^2)+(seb4_2^2))^.5
sebb5<-((seb5_1^2)+(seb5_2^2))^.5
sebb6<-((seb6_1^2)+(seb6_2^2))^.5
sebb7<-((seb7_1^2)+(seb7_2^2))^.5
sebb8<-((seb8_1^2)+(seb8_2^2))^.5
sebb9<-((seb9_1^2)+(seb9_2^2))^.5
sebb10<-((seb10_1^2)+(seb10_2^2))^.5
t1<-abs(abs(b1_1)-abs(b1_2))/sebb1
t2<-abs(abs(b2_1)-abs(b2_2))/sebb2
t3<-abs(abs(b3_1)-abs(b3_2))/sebb3
t4<-abs(abs(b4_1)-abs(b4_2))/sebb4
t5<-abs(abs(b5_1)-abs(b5_2))/sebb5
t6<-abs(abs(b6_1)-abs(b6_2))/sebb6
t7<-abs(abs(b7_1)-abs(b7_2))/sebb7
t8<-abs(abs(b8_1)-abs(b8_2))/sebb8
t9<-abs(abs(b9_1)-abs(b9_2))/sebb9
t10<-abs(abs(b10_1)-abs(b10_2))/sebb10
df1<-model1$df[2]+model2$df[2]
p1<-2*round(1-(pt(q=abs(t1), df=df1, lower.tail=TRUE)),3)
p2<-2*round(1-(pt(q=abs(t2), df=df1, lower.tail=TRUE)),3)
p3<-2*round(1-(pt(q=abs(t3), df=df1, lower.tail=TRUE)),3)
p4<-2*round(1-(pt(q=abs(t4), df=df1, lower.tail=TRUE)),3)
p5<-2*round(1-(pt(q=abs(t5), df=df1, lower.tail=TRUE)),3)
p6<-2*round(1-(pt(q=abs(t6), df=df1, lower.tail=TRUE)),3)
p7<-2*round(1-(pt(q=abs(t7), df=df1, lower.tail=TRUE)),3)
p8<-2*round(1-(pt(q=abs(t8), df=df1, lower.tail=TRUE)),3)
p9<-2*round(1-(pt(q=abs(t9), df=df1, lower.tail=TRUE)),3)
p10<-2*round(1-(pt(q=abs(t10), df=df1, lower.tail=TRUE)),3)
t1<-round((t1),3)
t2<-round((t2),3)
t3<-round((t3),3)
t4<-round((t4),3)
t5<-round((t5),3)
t6<-round((t6),3)
t7<-round((t7),3)
t8<-round((t8),3)
t9<-round((t9),3)
t10<-round((t10),3)
message("Predictor 1: "," t = ", t1,", p = ", p1)
message("Predictor 2: "," t = ", t2,", p = ", p2)
message("Predictor 3: "," t = ", t3,", p = ", p3)
message("Predictor 4: "," t = ", t4,", p = ", p4)
message("Predictor 5: "," t = ", t5,", p = ", p5)
message("Predictor 6: "," t = ", t6,", p = ", p6)
message("Predictor 7: "," t = ", t7,", p = ", p7)
message("Predictor 8: "," t = ", t8,", p = ", p8)
message("Predictor 9: "," t = ", t9,", p = ", p9)
message("Predictor 10: "," t = ", t10,", p = ", p10)
}
if ((pred =="2") && (comps=="raw")){
b1_1<-(model1$coefficients)[2,4]
b2_1<-(model1$coefficients)[3,4]
b1_2<-(model2$coefficients)[2,4]
b2_2<-(model2$coefficients)[3,4]
seb1_1<-(model1$coefficients)[2,2]
seb2_1<-(model1$coefficients)[3,2]
seb1_2<-(model2$coefficients)[2,2]
seb2_2<-(model2$coefficients)[3,2]
sebb1<-((seb1_1^2)+(seb1_2^2))^.5
sebb2<-((seb2_1^2)+(seb2_2^2))^.5
t1<-((b1_1-b1_2))/sebb1
t2<-((b2_1-b2_2))/sebb2
df1<-model1$df[2]+model2$df[2]
df2<-model2$df[2]
p1<-2*round(1-(pt(q=abs(t1), df=df1, lower.tail=TRUE)),3)
p2<-2*round(1-(pt(q=abs(t2), df=df2, lower.tail=TRUE)),3)
t1<-round((t1),3)
t2<-round((t2),3)
message("Predictor 1: "," t = ", t1,", p = ", p1)
message("Predictor 2: "," t = ", t2,", p = ", p2)
}
if ((pred =="3") && (comps=="raw")){
b1_1<-(model1$coefficients)[2,4]
b2_1<-(model1$coefficients)[3,4]
b3_1<-(model1$coefficients)[4,4]
b1_2<-(model2$coefficients)[2,4]
b2_2<-(model2$coefficients)[3,4]
b3_2<-(model2$coefficients)[4,4]
seb1_1<-(model1$coefficients)[2,2]
seb2_1<-(model1$coefficients)[3,2]
seb3_1<-(model1$coefficients)[4,2]
seb1_2<-(model2$coefficients)[2,2]
seb2_2<-(model2$coefficients)[3,2]
seb3_2<-(model2$coefficients)[4,2]
sebb1<-((seb1_1^2)+(seb1_2^2))^.5
sebb2<-((seb2_1^2)+(seb2_2^2))^.5
sebb3<-((seb3_1^2)+(seb3_2^2))^.5
t1<-((b1_1-b1_2))/sebb1
t2<-((b2_1-b2_2))/sebb2
t3<-((b3_1-b3_2))/sebb3
df1<-model1$df[2]+model2$df[2]
p1<-2*round(1-(pt(q=abs(t1), df=df1, lower.tail=TRUE)),3)
p2<-2*round(1-(pt(q=abs(t2), df=df1, lower.tail=TRUE)),3)
p3<-2*round(1-(pt(q=abs(t3), df=df1, lower.tail=TRUE)),3)
t1<-round((t1),3)
t2<-round((t2),3)
t3<-round((t3),3)
message("Predictor 1: "," t = ", t1,", p = ", p1)
message("Predictor 2: "," t = ", t2,", p = ", p2)
message("Predictor 3: "," t = ", t3,", p = ", p3)
}
if ((pred =="4") && (comps=="raw")){
b1_1<-(model1$coefficients)[2,4]
b2_1<-(model1$coefficients)[3,4]
b3_1<-(model1$coefficients)[4,4]
b4_1<-(model1$coefficients)[5,4]
b1_2<-(model2$coefficients)[2,4]
b2_2<-(model2$coefficients)[3,4]
b3_2<-(model2$coefficients)[4,4]
b4_2<-(model2$coefficients)[5,4]
seb1_1<-(model1$coefficients)[2,2]
seb2_1<-(model1$coefficients)[3,2]
seb3_1<-(model1$coefficients)[4,2]
seb4_1<-(model1$coefficients)[5,2]
seb1_2<-(model2$coefficients)[2,2]
seb2_2<-(model2$coefficients)[3,2]
seb3_2<-(model2$coefficients)[4,2]
seb4_2<-(model2$coefficients)[5,2]
sebb1<-((seb1_1^2)+(seb1_2^2))^.5
sebb2<-((seb2_1^2)+(seb2_2^2))^.5
sebb3<-((seb3_1^2)+(seb3_2^2))^.5
sebb4<-((seb4_1^2)+(seb4_2^2))^.5
t1<-((b1_1-b1_2))/sebb1
t2<-((b2_1-b2_2))/sebb2
t3<-((b3_1-b3_2))/sebb3
t4<-((b4_1-b4_2))/sebb4
df1<-model1$df[2]+model2$df[2]
p1<-2*round(1-(pt(q=abs(t1), df=df1, lower.tail=TRUE)),3)
p2<-2*round(1-(pt(q=abs(t2), df=df1, lower.tail=TRUE)),3)
p3<-2*round(1-(pt(q=abs(t3), df=df1, lower.tail=TRUE)),3)
p4<-2*round(1-(pt(q=abs(t4), df=df1, lower.tail=TRUE)),3)
t1<-round((t1),3)
t2<-round((t2),3)
t3<-round((t3),3)
t4<-round((t4),3)
message("Predictor 1: "," t = ", t1,", p = ", p1)
message("Predictor 2: "," t = ", t2,", p = ", p2)
message("Predictor 3: "," t = ", t3,", p = ", p3)
message("Predictor 4: "," t = ", t4,", p = ", p4)
}
if ((pred =="5") && (comps=="raw")){
b1_1<-(model1$coefficients)[2,4]
b2_1<-(model1$coefficients)[3,4]
b3_1<-(model1$coefficients)[4,4]
b4_1<-(model1$coefficients)[5,4]
b5_1<-(model1$coefficients)[6,4]
b1_2<-(model2$coefficients)[2,4]
b2_2<-(model2$coefficients)[3,4]
b3_2<-(model2$coefficients)[4,4]
b4_2<-(model2$coefficients)[5,4]
b5_2<-(model2$coefficients)[6,4]
seb1_1<-(model1$coefficients)[2,2]
seb2_1<-(model1$coefficients)[3,2]
seb3_1<-(model1$coefficients)[4,2]
seb4_1<-(model1$coefficients)[5,2]
seb5_1<-(model1$coefficients)[6,2]
seb1_2<-(model2$coefficients)[2,2]
seb2_2<-(model2$coefficients)[3,2]
seb3_2<-(model2$coefficients)[4,2]
seb4_2<-(model2$coefficients)[5,2]
seb5_2<-(model2$coefficients)[6,2]
sebb1<-((seb1_1^2)+(seb1_2^2))^.5
sebb2<-((seb2_1^2)+(seb2_2^2))^.5
sebb3<-((seb3_1^2)+(seb3_2^2))^.5
sebb4<-((seb4_1^2)+(seb4_2^2))^.5
sebb5<-((seb5_1^2)+(seb5_2^2))^.5
t1<-((b1_1-b1_2))/sebb1
t2<-((b2_1-b2_2))/sebb2
t3<-((b3_1-b3_2))/sebb3
t4<-((b4_1-b4_2))/sebb4
t5<-((b5_1-b5_2))/sebb5
df1<-model1$df[2]+model2$df[2]
p1<-2*round(1-(pt(q=abs(t1), df=df1, lower.tail=TRUE)),3)
p2<-2*round(1-(pt(q=abs(t2), df=df1, lower.tail=TRUE)),3)
p3<-2*round(1-(pt(q=abs(t3), df=df1, lower.tail=TRUE)),3)
p4<-2*round(1-(pt(q=abs(t4), df=df1, lower.tail=TRUE)),3)
p5<-2*round(1-(pt(q=abs(t5), df=df1, lower.tail=TRUE)),3)
t1<-round((t1),3)
t2<-round((t2),3)
t3<-round((t3),3)
t4<-round((t4),3)
t5<-round((t5),3)
message("Predictor 1: "," t = ", t1,", p = ", p1)
message("Predictor 2: "," t = ", t2,", p = ", p2)
message("Predictor 3: "," t = ", t3,", p = ", p3)
message("Predictor 4: "," t = ", t4,", p = ", p4)
message("Predictor 5: "," t = ", t5,", p = ", p5)
}
if ((pred =="6") && (comps=="raw")){
b1_1<-(model1$coefficients)[2,4]
b2_1<-(model1$coefficients)[3,4]
b3_1<-(model1$coefficients)[4,4]
b4_1<-(model1$coefficients)[5,4]
b5_1<-(model1$coefficients)[6,4]
b6_1<-(model1$coefficients)[7,4]
b1_2<-(model2$coefficients)[2,4]
b2_2<-(model2$coefficients)[3,4]
b3_2<-(model2$coefficients)[4,4]
b4_2<-(model2$coefficients)[5,4]
b5_2<-(model2$coefficients)[6,4]
b6_2<-(model2$coefficients)[7,4]
seb1_1<-(model1$coefficients)[2,2]
seb2_1<-(model1$coefficients)[3,2]
seb3_1<-(model1$coefficients)[4,2]
seb4_1<-(model1$coefficients)[5,2]
seb5_1<-(model1$coefficients)[6,2]
seb6_1<-(model1$coefficients)[7,2]
seb1_2<-(model2$coefficients)[2,2]
seb2_2<-(model2$coefficients)[3,2]
seb3_2<-(model2$coefficients)[4,2]
seb4_2<-(model2$coefficients)[5,2]
seb5_2<-(model2$coefficients)[6,2]
seb6_2<-(model2$coefficients)[7,2]
sebb1<-((seb1_1^2)+(seb1_2^2))^.5
sebb2<-((seb2_1^2)+(seb2_2^2))^.5
sebb3<-((seb3_1^2)+(seb3_2^2))^.5
sebb4<-((seb4_1^2)+(seb4_2^2))^.5
sebb5<-((seb5_1^2)+(seb5_2^2))^.5
sebb6<-((seb6_1^2)+(seb6_2^2))^.5
t1<-((b1_1-b1_2))/sebb1
t2<-((b2_1-b2_2))/sebb2
t3<-((b3_1-b3_2))/sebb3
t4<-((b4_1-b4_2))/sebb4
t5<-((b5_1-b5_2))/sebb5
t6<-((b6_1-b6_2))/sebb6
df1<-model1$df[2]+model2$df[2]
p1<-2*round(1-(pt(q=abs(t1), df=df1, lower.tail=TRUE)),3)
p2<-2*round(1-(pt(q=abs(t2), df=df1, lower.tail=TRUE)),3)
p3<-2*round(1-(pt(q=abs(t3), df=df1, lower.tail=TRUE)),3)
p4<-2*round(1-(pt(q=abs(t4), df=df1, lower.tail=TRUE)),3)
p5<-2*round(1-(pt(q=abs(t5), df=df1, lower.tail=TRUE)),3)
p6<-2*round(1-(pt(q=abs(t6), df=df1, lower.tail=TRUE)),3)
t1<-round((t1),3)
t2<-round((t2),3)
t3<-round((t3),3)
t4<-round((t4),3)
t5<-round((t5),3)
t6<-round((t6),3)
message("Predictor 1: "," t = ", t1,", p = ", p1)
message("Predictor 2: "," t = ", t2,", p = ", p2)
message("Predictor 3: "," t = ", t3,", p = ", p3)
message("Predictor 4: "," t = ", t4,", p = ", p4)
message("Predictor 5: "," t = ", t5,", p = ", p5)
message("Predictor 6: "," t = ", t6,", p = ", p6)
}
if ((pred =="7") && (comps=="raw")){
b1_1<-(model1$coefficients)[2,4]
b2_1<-(model1$coefficients)[3,4]
b3_1<-(model1$coefficients)[4,4]
b4_1<-(model1$coefficients)[5,4]
b5_1<-(model1$coefficients)[6,4]
b6_1<-(model1$coefficients)[7,4]
b7_1<-(model1$coefficients)[8,4]
b1_2<-(model2$coefficients)[2,4]
b2_2<-(model2$coefficients)[3,4]
b3_2<-(model2$coefficients)[4,4]
b4_2<-(model2$coefficients)[5,4]
b5_2<-(model2$coefficients)[6,4]
b6_2<-(model2$coefficients)[7,4]
b7_2<-(model2$coefficients)[8,4]
seb1_1<-(model1$coefficients)[2,2]
seb2_1<-(model1$coefficients)[3,2]
seb3_1<-(model1$coefficients)[4,2]
seb4_1<-(model1$coefficients)[5,2]
seb5_1<-(model1$coefficients)[6,2]
seb6_1<-(model1$coefficients)[7,2]
seb7_1<-(model1$coefficients)[8,2]
seb1_2<-(model2$coefficients)[2,2]
seb2_2<-(model2$coefficients)[3,2]
seb3_2<-(model2$coefficients)[4,2]
seb4_2<-(model2$coefficients)[5,2]
seb5_2<-(model2$coefficients)[6,2]
seb6_2<-(model2$coefficients)[7,2]
seb7_2<-(model2$coefficients)[8,2]
sebb1<-((seb1_1^2)+(seb1_2^2))^.5
sebb2<-((seb2_1^2)+(seb2_2^2))^.5
sebb3<-((seb3_1^2)+(seb3_2^2))^.5
sebb4<-((seb4_1^2)+(seb4_2^2))^.5
sebb5<-((seb5_1^2)+(seb5_2^2))^.5
sebb6<-((seb6_1^2)+(seb6_2^2))^.5
sebb7<-((seb7_1^2)+(seb7_2^2))^.5
t1<-((b1_1-b1_2))/sebb1
t2<-((b2_1-b2_2))/sebb2
t3<-((b3_1-b3_2))/sebb3
t4<-((b4_1-b4_2))/sebb4
t5<-((b5_1-b5_2))/sebb5
t6<-((b6_1-b6_2))/sebb6
t7<-((b7_1-b7_2))/sebb7
df1<-model1$df[2]+model2$df[2]
p1<-2*round(1-(pt(q=abs(t1), df=df1, lower.tail=TRUE)),3)
p2<-2*round(1-(pt(q=abs(t2), df=df1, lower.tail=TRUE)),3)
p3<-2*round(1-(pt(q=abs(t3), df=df1, lower.tail=TRUE)),3)
p4<-2*round(1-(pt(q=abs(t4), df=df1, lower.tail=TRUE)),3)
p5<-2*round(1-(pt(q=abs(t5), df=df1, lower.tail=TRUE)),3)
p6<-2*round(1-(pt(q=abs(t6), df=df1, lower.tail=TRUE)),3)
p7<-2*round(1-(pt(q=abs(t7), df=df1, lower.tail=TRUE)),3)
t1<-round((t1),3)
t2<-round((t2),3)
t3<-round((t3),3)
t4<-round((t4),3)
t5<-round((t5),3)
t6<-round((t6),3)
t7<-round((t7),3)
message("Predictor 1: "," t = ", t1,", p = ", p1)
message("Predictor 2: "," t = ", t2,", p = ", p2)
message("Predictor 3: "," t = ", t3,", p = ", p3)
message("Predictor 4: "," t = ", t4,", p = ", p4)
message("Predictor 5: "," t = ", t5,", p = ", p5)
message("Predictor 6: "," t = ", t6,", p = ", p6)
message("Predictor 7: "," t = ", t7,", p = ", p7)
}
if ((pred =="8") && (comps=="raw")){
b1_1<-(model1$coefficients)[2,4]
b2_1<-(model1$coefficients)[3,4]
b3_1<-(model1$coefficients)[4,4]
b4_1<-(model1$coefficients)[5,4]
b5_1<-(model1$coefficients)[6,4]
b6_1<-(model1$coefficients)[7,4]
b7_1<-(model1$coefficients)[8,4]
b8_1<-(model1$coefficients)[9,4]
b1_2<-(model2$coefficients)[2,4]
b2_2<-(model2$coefficients)[3,4]
b3_2<-(model2$coefficients)[4,4]
b4_2<-(model2$coefficients)[5,4]
b5_2<-(model2$coefficients)[6,4]
b6_2<-(model2$coefficients)[7,4]
b7_2<-(model2$coefficients)[8,4]
b8_2<-(model2$coefficients)[9,4]
seb1_1<-(model1$coefficients)[2,2]
seb2_1<-(model1$coefficients)[3,2]
seb3_1<-(model1$coefficients)[4,2]
seb4_1<-(model1$coefficients)[5,2]
seb5_1<-(model1$coefficients)[6,2]
seb6_1<-(model1$coefficients)[7,2]
seb7_1<-(model1$coefficients)[8,2]
seb8_1<-(model1$coefficients)[9,2]
seb1_2<-(model2$coefficients)[2,2]
seb2_2<-(model2$coefficients)[3,2]
seb3_2<-(model2$coefficients)[4,2]
seb4_2<-(model2$coefficients)[5,2]
seb5_2<-(model2$coefficients)[6,2]
seb6_2<-(model2$coefficients)[7,2]
seb7_2<-(model2$coefficients)[8,2]
seb8_2<-(model2$coefficients)[9,2]
sebb1<-((seb1_1^2)+(seb1_2^2))^.5
sebb2<-((seb2_1^2)+(seb2_2^2))^.5
sebb3<-((seb3_1^2)+(seb3_2^2))^.5
sebb4<-((seb4_1^2)+(seb4_2^2))^.5
sebb5<-((seb5_1^2)+(seb5_2^2))^.5
sebb6<-((seb6_1^2)+(seb6_2^2))^.5
sebb7<-((seb7_1^2)+(seb7_2^2))^.5
sebb8<-((seb8_1^2)+(seb8_2^2))^.5
t1<-((b1_1-b1_2))/sebb1
t2<-((b2_1-b2_2))/sebb2
t3<-((b3_1-b3_2))/sebb3
t4<-((b4_1-b4_2))/sebb4
t5<-((b5_1-b5_2))/sebb5
t6<-((b6_1-b6_2))/sebb6
t7<-((b7_1-b7_2))/sebb7
t8<-((b8_1-b8_2))/sebb8
df1<-model1$df[2]+model2$df[2]
p1<-2*round(1-(pt(q=abs(t1), df=df1, lower.tail=TRUE)),3)
p2<-2*round(1-(pt(q=abs(t2), df=df1, lower.tail=TRUE)),3)
p3<-2*round(1-(pt(q=abs(t3), df=df1, lower.tail=TRUE)),3)
p4<-2*round(1-(pt(q=abs(t4), df=df1, lower.tail=TRUE)),3)
p5<-2*round(1-(pt(q=abs(t5), df=df1, lower.tail=TRUE)),3)
p6<-2*round(1-(pt(q=abs(t6), df=df1, lower.tail=TRUE)),3)
p7<-2*round(1-(pt(q=abs(t7), df=df1, lower.tail=TRUE)),3)
p8<-2*round(1-(pt(q=abs(t8), df=df1, lower.tail=TRUE)),3)
t1<-round((t1),3)
t2<-round((t2),3)
t3<-round((t3),3)
t4<-round((t4),3)
t5<-round((t5),3)
t6<-round((t6),3)
t7<-round((t7),3)
t8<-round((t8),3)
message("Predictor 1: "," t = ", t1,", p = ", p1)
message("Predictor 2: "," t = ", t2,", p = ", p2)
message("Predictor 3: "," t = ", t3,", p = ", p3)
message("Predictor 4: "," t = ", t4,", p = ", p4)
message("Predictor 5: "," t = ", t5,", p = ", p5)
message("Predictor 6: "," t = ", t6,", p = ", p6)
message("Predictor 7: "," t = ", t7,", p = ", p7)
message("Predictor 8: "," t = ", t8,", p = ", p8)
}
if ((pred =="9") && (comps=="raw")){
b1_1<-(model1$coefficients)[2,4]
b2_1<-(model1$coefficients)[3,4]
b3_1<-(model1$coefficients)[4,4]
b4_1<-(model1$coefficients)[5,4]
b5_1<-(model1$coefficients)[6,4]
b6_1<-(model1$coefficients)[7,4]
b7_1<-(model1$coefficients)[8,4]
b8_1<-(model1$coefficients)[9,4]
b9_1<-(model1$coefficients)[10,4]
b1_2<-(model2$coefficients)[2,4]
b2_2<-(model2$coefficients)[3,4]
b3_2<-(model2$coefficients)[4,4]
b4_2<-(model2$coefficients)[5,4]
b5_2<-(model2$coefficients)[6,4]
b6_2<-(model2$coefficients)[7,4]
b7_2<-(model2$coefficients)[8,4]
b8_2<-(model2$coefficients)[9,4]
b9_2<-(model2$coefficients)[10,4]
seb1_1<-(model1$coefficients)[2,2]
seb2_1<-(model1$coefficients)[3,2]
seb3_1<-(model1$coefficients)[4,2]
seb4_1<-(model1$coefficients)[5,2]
seb5_1<-(model1$coefficients)[6,2]
seb6_1<-(model1$coefficients)[7,2]
seb7_1<-(model1$coefficients)[8,2]
seb8_1<-(model1$coefficients)[9,2]
seb9_1<-(model1$coefficients)[10,2]
seb1_2<-(model2$coefficients)[2,2]
seb2_2<-(model2$coefficients)[3,2]
seb3_2<-(model2$coefficients)[4,2]
seb4_2<-(model2$coefficients)[5,2]
seb5_2<-(model2$coefficients)[6,2]
seb6_2<-(model2$coefficients)[7,2]
seb7_2<-(model2$coefficients)[8,2]
seb8_2<-(model2$coefficients)[9,2]
seb9_2<-(model2$coefficients)[10,2]
sebb1<-((seb1_1^2)+(seb1_2^2))^.5
sebb2<-((seb2_1^2)+(seb2_2^2))^.5
sebb3<-((seb3_1^2)+(seb3_2^2))^.5
sebb4<-((seb4_1^2)+(seb4_2^2))^.5
sebb5<-((seb5_1^2)+(seb5_2^2))^.5
sebb6<-((seb6_1^2)+(seb6_2^2))^.5
sebb7<-((seb7_1^2)+(seb7_2^2))^.5
sebb8<-((seb8_1^2)+(seb8_2^2))^.5
sebb9<-((seb9_1^2)+(seb9_2^2))^.5
t1<-((b1_1-b1_2))/sebb1
t2<-((b2_1-b2_2))/sebb2
t3<-((b3_1-b3_2))/sebb3
t4<-((b4_1-b4_2))/sebb4
t5<-((b5_1-b5_2))/sebb5
t6<-((b6_1-b6_2))/sebb6
t7<-((b7_1-b7_2))/sebb7
t8<-((b8_1-b8_2))/sebb8
t9<-((b9_1-b9_2))/sebb9
df1<-model1$df[2]+model2$df[2]
p1<-2*round(1-(pt(q=abs(t1), df=df1, lower.tail=TRUE)),3)
p2<-2*round(1-(pt(q=abs(t2), df=df1, lower.tail=TRUE)),3)
p3<-2*round(1-(pt(q=abs(t3), df=df1, lower.tail=TRUE)),3)
p4<-2*round(1-(pt(q=abs(t4), df=df1, lower.tail=TRUE)),3)
p5<-2*round(1-(pt(q=abs(t5), df=df1, lower.tail=TRUE)),3)
p6<-2*round(1-(pt(q=abs(t6), df=df1, lower.tail=TRUE)),3)
p7<-2*round(1-(pt(q=abs(t7), df=df1, lower.tail=TRUE)),3)
p8<-2*round(1-(pt(q=abs(t8), df=df1, lower.tail=TRUE)),3)
p9<-2*round(1-(pt(q=abs(t9), df=df1, lower.tail=TRUE)),3)
t1<-round((t1),3)
t2<-round((t2),3)
t3<-round((t3),3)
t4<-round((t4),3)
t5<-round((t5),3)
t6<-round((t6),3)
t7<-round((t7),3)
t8<-round((t8),3)
t9<-round((t9),3)
message("Predictor 1: "," t = ", t1,", p = ", p1)
message("Predictor 2: "," t = ", t2,", p = ", p2)
message("Predictor 3: "," t = ", t3,", p = ", p3)
message("Predictor 4: "," t = ", t4,", p = ", p4)
message("Predictor 5: "," t = ", t5,", p = ", p5)
message("Predictor 6: "," t = ", t6,", p = ", p6)
message("Predictor 7: "," t = ", t7,", p = ", p7)
message("Predictor 8: "," t = ", t8,", p = ", p8)
message("Predictor 9: "," t = ", t9,", p = ", p9)
}
if ((pred =="10") && (comps=="raw")){
b1_1<-(model1$coefficients)[2,4]
b2_1<-(model1$coefficients)[3,4]
b3_1<-(model1$coefficients)[4,4]
b4_1<-(model1$coefficients)[5,4]
b5_1<-(model1$coefficients)[6,4]
b6_1<-(model1$coefficients)[7,4]
b7_1<-(model1$coefficients)[8,4]
b8_1<-(model1$coefficients)[9,4]
b9_1<-(model1$coefficients)[10,4]
b10_1<-(model1$coefficients)[11,4]
b1_2<-(model2$coefficients)[2,4]
b2_2<-(model2$coefficients)[3,4]
b3_2<-(model2$coefficients)[4,4]
b4_2<-(model2$coefficients)[5,4]
b5_2<-(model2$coefficients)[6,4]
b6_2<-(model2$coefficients)[7,4]
b7_2<-(model2$coefficients)[8,4]
b8_2<-(model2$coefficients)[9,4]
b9_2<-(model2$coefficients)[10,4]
b10_2<-(model2$coefficients)[11,4]
seb1_1<-(model1$coefficients)[2,2]
seb2_1<-(model1$coefficients)[3,2]
seb3_1<-(model1$coefficients)[4,2]
seb4_1<-(model1$coefficients)[5,2]
seb5_1<-(model1$coefficients)[6,2]
seb6_1<-(model1$coefficients)[7,2]
seb7_1<-(model1$coefficients)[8,2]
seb8_1<-(model1$coefficients)[9,2]
seb9_1<-(model1$coefficients)[10,2]
seb10_1<-(model1$coefficients)[11,2]
seb1_2<-(model2$coefficients)[2,2]
seb2_2<-(model2$coefficients)[3,2]
seb3_2<-(model2$coefficients)[4,2]
seb4_2<-(model2$coefficients)[5,2]
seb5_2<-(model2$coefficients)[6,2]
seb6_2<-(model2$coefficients)[7,2]
seb7_2<-(model2$coefficients)[8,2]
seb8_2<-(model2$coefficients)[9,2]
seb9_2<-(model2$coefficients)[10,2]
seb10_2<-(model2$coefficients)[11,2]
sebb1<-((seb1_1^2)+(seb1_2^2))^.5
sebb2<-((seb2_1^2)+(seb2_2^2))^.5
sebb3<-((seb3_1^2)+(seb3_2^2))^.5
sebb4<-((seb4_1^2)+(seb4_2^2))^.5
sebb5<-((seb5_1^2)+(seb5_2^2))^.5
sebb6<-((seb6_1^2)+(seb6_2^2))^.5
sebb7<-((seb7_1^2)+(seb7_2^2))^.5
sebb8<-((seb8_1^2)+(seb8_2^2))^.5
sebb9<-((seb9_1^2)+(seb9_2^2))^.5
sebb10<-((seb10_1^2)+(seb10_2^2))^.5
t1<-((b1_1-b1_2))/sebb1
t2<-((b2_1-b2_2))/sebb2
t3<-((b3_1-b3_2))/sebb3
t4<-((b4_1-b4_2))/sebb4
t5<-((b5_1-b5_2))/sebb5
t6<-((b6_1-b6_2))/sebb6
t7<-((b7_1-b7_2))/sebb7
t8<-((b8_1-b8_2))/sebb8
t9<-((b9_1-b9_2))/sebb9
t10<-((b10_1-b10_2))/sebb10
df1<-model1$df[2]+model2$df[2]
p1<-2*round(1-(pt(q=abs(t1), df=df1, lower.tail=TRUE)),3)
p2<-2*round(1-(pt(q=abs(t2), df=df1, lower.tail=TRUE)),3)
p3<-2*round(1-(pt(q=abs(t3), df=df1, lower.tail=TRUE)),3)
p4<-2*round(1-(pt(q=abs(t4), df=df1, lower.tail=TRUE)),3)
p5<-2*round(1-(pt(q=abs(t5), df=df1, lower.tail=TRUE)),3)
p6<-2*round(1-(pt(q=abs(t6), df=df1, lower.tail=TRUE)),3)
p7<-2*round(1-(pt(q=abs(t7), df=df1, lower.tail=TRUE)),3)
p8<-2*round(1-(pt(q=abs(t8), df=df1, lower.tail=TRUE)),3)
p9<-2*round(1-(pt(q=abs(t9), df=df1, lower.tail=TRUE)),3)
p10<-2*round(1-(pt(q=abs(t10), df=df1, lower.tail=TRUE)),3)
t1<-round((t1),3)
t2<-round((t2),3)
t3<-round((t3),3)
t4<-round((t4),3)
t5<-round((t5),3)
t6<-round((t6),3)
t7<-round((t7),3)
t8<-round((t8),3)
t9<-round((t9),3)
t10<-round((t10),3)
message("Predictor 1: "," t = ", t1,", p = ", p1)
message("Predictor 2: "," t = ", t2,", p = ", p2)
message("Predictor 3: "," t = ", t3,", p = ", p3)
message("Predictor 4: "," t = ", t4,", p = ", p4)
message("Predictor 5: "," t = ", t5,", p = ", p5)
message("Predictor 6: "," t = ", t6,", p = ", p6)
message("Predictor 7: "," t = ", t7,", p = ", p7)
message("Predictor 8: "," t = ", t8,", p = ", p8)
message("Predictor 9: "," t = ", t9,", p = ", p9)
message("Predictor 10: "," t = ", t10,", p = ", p10)
}
}
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