Description Author(s) References See Also Examples
Exam5.1 is used to show polynomial multiple regression with binomial response
Muhammad Yaseen (myaseen208@gmail.com)
Adeela Munawar (adeela.uaf@gmail.com)
Stroup, W. W. (2012). Generalized Linear Mixed Models: Modern Concepts, Methods and Applications. CRC Press.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 | ##---Sequential Fit of the logit Model
Exam5.1.glm.1 <-
glm(
formula = F/N~ X
, family = quasibinomial(link = "logit")
, data = DataSet5.1
, weights = NULL
# , subset
# , na.action
, start = NULL
# , etastart
# , mustart
# , offset
# , control = list(...)
# , model = TRUE
, method = "glm.fit"
# , x = FALSE
# , y = TRUE
, contrasts = NULL
# , ...
)
summary(Exam5.1.glm.1)
## confint.default() produce Wald Confidence interval as SAS produces
##---Likelihood Ratio test for Model 1
(LRExam5.1.glm.1 <-
anova(
object = Exam5.1.glm.1
, test = "Chisq")
)
library(aod)
WaldExam5.1.glm.1 <-
wald.test(
Sigma = vcov(object=Exam5.1.glm.1)
, b = coef(object=Exam5.1.glm.1)
, Terms = 2
, L = NULL
, H0 = NULL
, df = NULL
, verbose = FALSE
)
##---Sequential Fit of the logit Model quadratic terms involved
Exam5.1.glm.2 <-
glm(
formula = F/N~ X + I(X^2)
, family = quasibinomial(link = "logit")
, data = DataSet5.1
, weights = NULL
# , subset
# , na.action
, start = NULL
# , etastart
# , mustart
# , offset
# , control = list(...)
# , model = TRUE
, method = "glm.fit"
# , x = FALSE
# , y = TRUE
, contrasts = NULL
# , ...
)
summary( Exam5.1.glm.2 )
##---Likelihood Ratio test for Model Exam5.1.glm.2
(LRExam5.1.glm.2 <-
anova(
object = Exam5.1.glm.2
, test = "Chisq")
)
WaldExam5.1.glm.2 <-
wald.test(
Sigma = vcov(object=Exam5.1.glm.2)
, b = coef(object=Exam5.1.glm.2)
, Terms = 3
, L = NULL
, H0 = NULL
, df = NULL
, verbose = FALSE
)
##---Sequential Fit of the logit Model 5th power terms involved
Exam5.1.glm.3 <-
glm(
formula = F/N~ X + I(X^2) + I(X^3) + I(X^4) + I(X^5)
, family = quasibinomial(link = "logit")
, data = DataSet5.1
, weights = NULL
# , subset
# , na.action
, start = NULL
# , etastart
# , mustart
# , offset
# , control = list(...)
# , model = TRUE
, method = "glm.fit"
# , x = FALSE
# , y = TRUE
, contrasts = NULL
# , ...
)
summary(Exam5.1.glm.3)
## confint.default() produce Wald Confidence interval as SAS produces
##---Likelihood Ratio test for Model 1
(LRExam5.1.glm.3 <-
anova(
object = Exam5.1.glm.3
, test = "Chisq")
)
WaldExam5.1.glm.3 <-
wald.test(
Sigma = vcov(object=Exam5.1.glm.3)
, b = coef(object=Exam5.1.glm.3)
, Terms = 6
, L = NULL
, H0 = NULL
, df = NULL
, verbose = FALSE
)
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