In ddarmon/confdist: confdist, a package for creating confidence functions

Confidence Curve Weight Change

Basic Stats For Low Carb

n_lowcarb <- length(weight_change_data$weightchange[weight_change_data$diet=="Low Carb"])

mean_lowcarb <- mean(weight_change_data$weightchange[weight_change_data$diet=="Low Carb"])

sd_lowcarb <- sd(weight_change_data$weightchange[weight_change_data$diet=="Low Carb"])

lowcarb.bottom <- sd_lowcarb/sqrt(n_lowcarb)

mean_lowcarb

Low Carb Confidence Distribution

curve(1-pt(((mean_lowcarb-mu)/lowcarb.bottom),df=n_lowcarb-1),from = -20, to=0,xname = "mu")

lowcarb.t.test <- t.test(weight_change_data$weightchange[weight_change_data$diet=="Low Carb"], alternative = "greater", mu= -12.5)

lowcarb.t.test$p.value

curve(1-pt(((mean_lowcarb-mu)/lowcarb.bottom),df=n_lowcarb-1),from = -20, to=0,xname = "mu") 
abline(h=lowcarb.t.test$p.value)
abline(v=-12.5)

shows the pvalues for a right sides test

Checking Low Carb Confidence Distribution

curve(1-pt(((mean_lowcarb-mu)/lowcarb.bottom),df=n_lowcarb-1),from = -20, to=0,xname = "mu")
for (mu in seq(from=-20, to=0, by=1)){ 
  lowcarb.t.test <-t.test(weight_change_data$weightchange[weight_change_data$diet=="Low Carb"], alternative = "greater", mu= mu)
abline(h=lowcarb.t.test$p.value, v=mu)
  }

Low Carb Confidence Curve

conf.curve.lowcarb <- function(mu)abs(2*(1-pt(((mean_lowcarb-mu)/lowcarb.bottom),df=n_lowcarb-1))-1)
curve(conf.curve.lowcarb(mu),from=-20, to =0 ,xname = "mu")

Checking Low Carb Confidence Curve

curve(conf.curve.lowcarb(mu),from=-20, to =0 ,xname = "mu")
for (conf.int in seq(from=0 , to=1, by=.1)) {
  lowcarb.test.conf <-t.test(weight_change_data$weightchange[weight_change_data$diet=="Low Carb"], conf.level = conf.int)
  abline(v=lowcarb.test.conf$conf.int, h=conf.int)
}

abline(v=lowcarb.test.conf$conf.int, h=.8)

Confidence Density Low Carb

lowcarb.conf.dens <- function(mu)1/(sd_lowcarb/sqrt(n_lowcarb))*dt((mean_lowcarb-mu)/(lowcarb.bottom), df=n_lowcarb-1)

curve(lowcarb.conf.dens(mu), from=-20, to=0, xname = "mu")

Checking Confidence Density Low Carb

curve(1-pt(((mean_lowcarb-mu)/lowcarb.bottom),df=n_lowcarb-1),from = -20, to=0,xname = "mu")
for (upper in seq(from=-20, to=0, by=.5)) {
  area <- integrate(function(mu)lowcarb.conf.dens(mu), lower=-Inf, upper=upper)$value
  abline(v=upper, col="red")
  abline(h=area, col="blue")

}

Basic Stats For Low Fat

n_lowfat <- length(weight_change_data$weightchange[weight_change_data$diet=="Low Fat"])

mean_lowfat<- mean(weight_change_data$weightchange[weight_change_data$diet=="Low Fat"])

sd_lowfat <- sd(weight_change_data$weightchange[weight_change_data$diet=="Low Fat"])

lowfat.bottom <- sd_lowfat/sqrt(305)

Low Fat Confidence Distribution

curve(1-pt(((mean_lowfat-mu)/lowfat),df=304),from = -20, to=0,xname = "mu")

lowfat.t.test <- t.test(weight_change_data$weightchange[weight_change_data$diet=="Low Fat"], alternative = "greater", mu= -12.5)

lowfat.t.test$p.value

curve(1-pt(((mean_lowfat-mu)/lowfat.bottom),df=n_lowfat-1),from = -20, to=0,xname = "mu") 
abline(h=lowfat.t.test$p.value)
abline(v=-12.5)

Checking Low Fat Confidence Distribution

curve(1-pt(((mean_lowfat-mu)/lowfat.bottom),df=n_lowfat-1),from = -20, to=0,xname = "mu")
for (mu in seq(from=-20, to=0, by=1)){ 
  lowfat.t.test <-t.test(weight_change_data$weightchange[weight_change_data$diet=="Low Fat"], alternative = "greater", mu= mu)
abline(h=lowfat.t.test$p.value, v=mu)
  }

Low Carb Confidence Curve

conf.curve.lowfat <- function(mu)abs(2*(1-pt(((mean_lowfat-mu)/lowfat.bottom),df=n_lowfat-1))-1)

curve(conf.curve.lowfat(mu),from=-20, to =0 ,xname = "mu")

Checking Low Fat Confidence Curve

curve(conf.curve.lowfat(mu),from=-20, to =0 ,xname = "mu")
for (conf.int in seq(from=0 , to=1, by=.1)) {
  lowfat.test.conf <-t.test(weight_change_data$weightchange[weight_change_data$diet=="Low Fat"], conf.level = conf.int)
  abline(v=lowfat.test.conf$conf.int, h=conf.int)
}

abline(v=lowfat.test.conf$conf.int, h=.8)

Confidence Density Low Fat

lowfat.conf.dens <- function(mu)1/(sd_lowfat/sqrt(n_lowfat))*dt((mean_lowfat-mu)/(lowfat.bottom), df=n_lowfat-1)

curve(lowfat.conf.dens(mu), from=-20, to=0, xname = "mu")

Checking Confidence Density Low Fat

curve(1-pt(((mean_lowfat-mu)/lowfat.bottom),df=n_lowfat-1),from = -20, to=0,xname = "mu")
for (upper in seq(from=-20, to=0, by=.5)) {
  area <- integrate(function(mu)lowfat.conf.dens(mu), lower=-Inf, upper=upper)$value
  abline(v=upper, col="red")
  abline(h=area, col="blue")

}

Confidence Distribution Two Sample T-test

curve(1-pt((((mean_lowcarb-mean_lowfat)-delta)/sqrt((sd_lowcarb^2/n_lowcarb)+(sd_lowfat^2/n_lowfat))),df=603.97),from = -10, to=10, xname = "delta")

Validate Confidence Qualities

two.test <-t.test(weight_change_data$weightchange[weight_change_data$diet=="Low Carb"], weight_change_data$weightchange[weight_change_data$diet=="Low Fat"], alternative = "greater", mu= -2)

two.test$p.value

curve(1-pt((((mean_lowcarb-mean_lowfat)-delta)/sqrt((sd_lowcarb^2/n_lowcarb)+(sd_lowfat^2/n_lowfat))),df=603.97),from = -10, to=10,xname = "delta", ylab = "p.values")
for (delta in seq(from=-10, to=10, by=1)) {
  two.test <- t.test(weight_change_data$weightchange[weight_change_data$diet=="Low Carb"], weight_change_data$weightchange[weight_change_data$diet=="Low Fat"], alternative = "greater", mu= delta)$p.value
  abline(h=two.test, col="red")
  abline(v=delta, col="blue")
}

Confidence Curve for Two Sample T Test

conf.curve.two <- function(delta)abs(2*(1-pt((((mean_lowcarb-mean_lowfat)-delta)/sqrt((sd_lowcarb^2/n_lowcarb)+(sd_lowfat^2/n_lowfat))),df=603.97))-1)

curve(conf.curve.two(delta),from=-10, to =10 ,xname = "delta")

two.conf <- t.test(weight_change_data$weightchange[weight_change_data$diet=="Low Carb"],weight_change_data$weightchange[weight_change_data$diet=="Low Fat"], conf.level = .95)
  abline(v=two.conf$conf.int, h=.95)

Confidence Density For Two Sample T Test

conf.dens.two <- function(delta)1/(sqrt((sd_lowcarb^2/n_lowcarb)+(sd_lowfat^2/n_lowfat)))*dt((((mean_lowcarb-mean_lowfat)-delta)/sqrt((sd_lowcarb^2/n_lowcarb)+(sd_lowfat^2/n_lowfat))),df=603.97)

curve(conf.dens.two(delta), from=-10, to=10, xname = "delta")
area <- integrate(function()lowfat.conf.dens(mu), lower=-Inf, upper=upper)$value
  abline(v=upper, col="red")
  abline(h=area, col="blue")

ddarmon/confdist documentation built on Aug. 8, 2020, 4:44 p.m.