## ------------------------------------------------------------------------ library("medflex") data("UPBdata") head(UPBdata) ## ------------------------------------------------------------------------ medFit <- glm(negaff ~ factor(attbin) + gender + educ + age, family = gaussian, data = UPBdata) ## ------------------------------------------------------------------------ expData <- neWeight(medFit) ## ------------------------------------------------------------------------ head(expData, 4) ## ------------------------------------------------------------------------ expData <- neWeight(negaff ~ factor(attbin) + gender + educ + age, data = UPBdata) ## ------------------------------------------------------------------------ w <- weights(expData) head(w, 10) ## ------------------------------------------------------------------------ set.seed(1234) neMod1 <- neModel(UPB ~ attbin0 + attbin1 + gender + educ + age, family = binomial("logit"), expData = expData) summary(neMod1) ## ------------------------------------------------------------------------ neMod1 <- neModel(UPB ~ attbin0 + attbin1 + gender + educ + age, family = binomial("logit"), expData = expData, se = "robust") summary(neMod1) ## ------------------------------------------------------------------------ exp(confint(neMod1)[c("attbin01", "attbin11"), ]) ## ------------------------------------------------------------------------ impFit <- glm(UPB ~ factor(attbin) + negaff + gender + educ + age, family = binomial("logit"), data = UPBdata) ## ----warning = F--------------------------------------------------------- expData <- neImpute(impFit) ## ------------------------------------------------------------------------ expData <- neImpute(UPB ~ factor(attbin) + negaff + gender + educ + age, family = binomial("logit"), data = UPBdata) ## ------------------------------------------------------------------------ head(expData, 4) ## ----results = hide------------------------------------------------------ neMod1 <- neModel(UPB ~ attbin0 + attbin1 + gender + educ + age, family = binomial("logit"), expData = expData, se = "robust") ## ------------------------------------------------------------------------ summary(neMod1) ## ------------------------------------------------------------------------ expData <- neImpute(UPB ~ attcat + negaff + gender + educ + age, family = binomial, data = UPBdata) head(expData) ## ------------------------------------------------------------------------ neMod <- neModel(UPB ~ attcat0 + attcat1 + gender + educ + age, family = binomial, expData = expData, se = "robust") summary(neMod) ## ------------------------------------------------------------------------ library("car") Anova(neMod) ## ------------------------------------------------------------------------ expData <- neImpute(UPB ~ att + negaff + gender + educ + age, family = binomial("logit"), data = UPBdata, nRep = 3) head(expData) ## ------------------------------------------------------------------------ neMod1 <- neModel(UPB ~ att0 + att1 + gender + educ + age, family = binomial("logit"), expData = expData, se = "robust") summary(neMod1) ## ------------------------------------------------------------------------ expData <- neImpute(UPB ~ att * negaff + gender + educ + age, family = binomial("logit"), data = UPBdata) neMod2 <- neModel(UPB ~ att0 * att1 + gender + educ + age, family = binomial("logit"), expData = expData, se = "robust") summary(neMod2) ## ------------------------------------------------------------------------ impData <- neImpute(UPB ~ (att + negaff) * gender + educ + age, family = binomial("logit"), data = UPBdata) neMod3 <- neModel(UPB ~ att0 + att1 * gender + educ + age, family = binomial("logit"), expData = impData, se = "robust") summary(neMod3) ## ------------------------------------------------------------------------ impData <- neImpute(UPB ~ (att + negaff) * educ + gender + age, family = binomial("logit"), data = UPBdata) neMod4 <- neModel(UPB ~ (att0 + att1) * educ + gender + age, family = binomial("logit"), expData = impData, se = "robust") ## ------------------------------------------------------------------------ lht <- neLht(neMod2, linfct = c("att0 + att0:att1 = 0", "att1 + att0:att1 = 0", "att0 + att1 + att0:att1 = 0")) ## ------------------------------------------------------------------------ exp(cbind(coef(lht), confint(lht))) ## ------------------------------------------------------------------------ summary(lht) ## ------------------------------------------------------------------------ effdecomp <- neEffdecomp(neMod2) summary(effdecomp) ## ------------------------------------------------------------------------ neEffdecomp(neMod3) neEffdecomp(neMod3, covLev = c(gender = "M")) ## ----label=plot2,include=FALSE------------------------------------------- par(mfrow = c(1, 2)) plot(neMod2, xlab = "log odds ratio") plot(neMod2, xlab = "odds ratio", transf = exp) ## ----label=fig2,fig=TRUE,echo=FALSE,height=3.6,width=9------------------- par(mfrow = c(1, 2)) plot(neMod2, xlab = "log odds ratio") plot(neMod2, xlab = "odds ratio", transf = exp) ## ------------------------------------------------------------------------ modmed <- neLht(neMod4, linfct = c("att1:educM = 0", "att1:educH = 0")) summary(modmed, test = Chisqtest()) ## ------------------------------------------------------------------------ expFit <- glm(att ~ gender + educ + age, data = UPBdata) ## ------------------------------------------------------------------------ impData <- neImpute(UPB ~ att + negaff + gender + educ + age, family = binomial("logit"), data = UPBdata) ## ------------------------------------------------------------------------ neMod5 <- neModel(UPB ~ att0 + att1, family = binomial("logit"), expData = impData, xFit = expFit, se = "robust") summary(neMod5) ## ----echo = F------------------------------------------------------------ de <- neLht(neMod5, c("att0 = 0")) ie <- neLht(neMod5, c("att1 = 0")) ## ------------------------------------------------------------------------ impData <- neImpute(UPB ~ att + initiator * negaff + gender + educ + age, family = binomial("logit"), nMed = 2, data = UPBdata) ## ------------------------------------------------------------------------ neMod6 <- neModel(UPB ~ att0 + att1 + gender + educ + age, family = binomial("logit"), expData = impData, se = "robust") summary(neMod6) ## ------------------------------------------------------------------------ library("mice") library("mitools") set.seed(123) missdat <- UPBdata for (i in 1:ncol(missdat)) { missdat[sample(nrow(missdat))[1:10], i] <- NA } multImp <- mice(missdat, m = 10) expData <- with(multImp, neWeight(negaff ~ factor(attbin) + gender + educ + age)) expData <- imputationList(expData$analyses) neMod1 <- with(expData, neModel(UPB ~ attbin0 + attbin1 + gender + educ + age, family = binomial("logit"), se = "robust")) MIcombine(neMod1)