### R code from vignette source 'IntroductionIndividualDataFurtherExamples.rnw' ################################################### ### code chunk number 1: IntroductionIndividualDataFurtherExamples.rnw:80-91 ################################################### library("ISLR") data("Wage") Wage2 <- Wage[Wage$age >= 25 & Wage$age <= 55, ] names(Wage2)[names(Wage2) %in% c("year","age")] <- c("period","age") cohort <- Wage2$period - Wage2$age indust_job <- ifelse(Wage2$jobclass=="1. Industrial", 1, 0) hasdegree <- ifelse(Wage2$education %in% c("4. College Grad", "5. Advanced Degree"), 1, 0) married <- ifelse(Wage2$maritl == "2. Married", 1, 0) Wage3 <- cbind(Wage2, cohort, indust_job, hasdegree, married) rm(Wage, Wage2, cohort, indust_job, hasdegree, married) ################################################### ### code chunk number 2: IntroductionIndividualDataFurtherExamples.rnw:95-99 ################################################### library("plyr") library("apc") model1 <- apc.indiv.est.model(Wage3, dep.var="logwage") apc.plot.fit(model1) ################################################### ### code chunk number 3: IntroductionIndividualDataFurtherExamples.rnw:103-109 ################################################### model2 <- apc.indiv.est.model(Wage3, dep.var = "married", covariates = c("logwage", "hasdegree"), model.design = "AC", model.family = "binomial") apc.plot.fit(model2) model2$coefficients.covariates ################################################### ### code chunk number 4: IntroductionIndividualDataFurtherExamples.rnw:113-122 ################################################### Wage3_cc <- Wage3[Wage3$cohort>1950 & Wage3$cohort<1982, ] model3 <- apc.indiv.est.model(Wage3_cc, dep.var = "married", covariates = c("logwage", "hasdegree"), model.design = "AC", model.family = "binomial", n.coh.excl.end = 3, n.coh.excl.start = 3) apc.plot.fit(model3) model3$coefficients.covariates ################################################### ### code chunk number 5: IntroductionIndividualDataFurtherExamples.rnw:126-128 ################################################### library("car") linearHypothesis(model3$fit, "logwage = hasdegree", test="F") ################################################### ### code chunk number 6: IntroductionIndividualDataFurtherExamples.rnw:132-139 ################################################### model4 <- apc.indiv.est.model(Wage3_cc, dep.var = "hasdegree", model.family = "binomial", covariates = "logwage", model.design = "TS", n.coh.excl.start = 3, n.coh.excl.end = 3) model4$result ################################################### ### code chunk number 7: IntroductionIndividualDataFurtherExamples.rnw:143-154 ################################################### myspec2 <- list(20,30,.002,"ols",.Machine$double.eps,.002,NULL,NULL) names(myspec2) <- c("maxit.loop", "maxit.linesearch", "tolerance", "init", "inv.tol", "d1.tol", "custom.kappa", "custom.zeta") model4b <- apc.indiv.est.model(Wage3_cc, dep.var = "hasdegree", model.family = "binomial", covariates = "logwage", model.design = "TS", n.coh.excl.start = 3, n.coh.excl.end = 3, NR.controls = myspec2) model4b$result ################################################### ### code chunk number 8: IntroductionIndividualDataFurtherExamples.rnw:158-164 ################################################### library("survey") inv_wt <- runif(nrow(Wage3), 0, 1) Wage_wt <- cbind(Wage3, inv_wt) model5 <- apc.indiv.est.model(Wage_wt, dep.var = "logwage", wt.var= "inv_wt") apc.plot.fit(model5) ################################################### ### code chunk number 9: IntroductionIndividualDataFurtherExamples.rnw:172-185 ################################################### library("AER") data("PSID7682") period <- as.numeric(PSID7682$year) + 1975 entry <- period - PSID7682$experience logwage <- log(PSID7682$wage) inunion <- ifelse(PSID7682$union == "yes", 1, 0) insouth <- ifelse(PSID7682$south == "yes", 1, 0) psid2 <- cbind(PSID7682, period, entry, logwage, inunion, insouth) names(psid2)[names(psid2) %in% c("experience", "entry")] <- c("age", "cohort") psid3 <- psid2[psid2$cohort >=1939, ] rm(PSID7682, period, entry, logwage, inunion, insouth, psid2) ################################################### ### code chunk number 10: IntroductionIndividualDataFurtherExamples.rnw:189-196 ################################################### library("plm") model6 <- apc.indiv.est.model(psid3, dep.var = "logwage", covariates = c("inunion", "insouth"), plmmodel = "within", id.var = "id", model.design = "FAP") apc.plot.fit(model6) model6$coefficients.covariates ################################################### ### code chunk number 11: IntroductionIndividualDataFurtherExamples.rnw:200-204 ################################################### model6b <- apc.indiv.est.model(psid3, dep.var = "logwage", plmmodel = "within", id.var = "id", model.design = "FAP") waldtest(model6$fit, model6b$fit) ################################################### ### code chunk number 12: IntroductionIndividualDataFurtherExamples.rnw:208-220 ################################################### collinear_1 <- apc.indiv.design.collinear(psid3) design_1 <- apc.indiv.design.model(collinear_1, dep.var = "logwage", covariates = c("inunion", "insouth"), plmmodel = "random", id.var ="id") plm_1 <- plm(design_1$model.formula, data = collinear_1$full.design.collinear, index = c("id", "period"), model = "random") design_2 <- apc.indiv.design.model(collinear_1, dep.var = "logwage", plmmodel = "random", id.var ="id") fit_2 <- apc.indiv.fit.model(design_2) waldtest(plm_1, fit_2$fit, test="F") ################################################### ### code chunk number 13: IntroductionIndividualDataFurtherExamples.rnw:231-242 ################################################### library("ISLR") data("Wage") Wage2 <- Wage[Wage$age >= 25 & Wage$age <= 55, ] names(Wage2)[names(Wage2) %in% c("year","age")] <- c("period","age") cohort <- Wage2$period - Wage2$age indust_job <- ifelse(Wage2$jobclass=="1. Industrial", 1, 0) hasdegree <- ifelse(Wage2$education %in% c("4. College Grad", "5. Advanced Degree"), 1, 0) married <- ifelse(Wage2$maritl == "2. Married", 1, 0) Wage3 <- cbind(Wage2, cohort, indust_job, hasdegree, married) rm(Wage, Wage2, cohort, indust_job, hasdegree, married) ################################################### ### code chunk number 14: IntroductionIndividualDataFurtherExamples.rnw:246-251 ################################################### test1 <- apc.indiv.model.table(Wage3, dep.var="logwage", test= "Wald", dist="F", model.family="gaussian", TS=TRUE) test1$table ################################################### ### code chunk number 15: IntroductionIndividualDataFurtherExamples.rnw:255-261 ################################################### test2 <- apc.indiv.model.table(Wage3, dep.var="married", covariates = "hasdegree", test="LR", dist="Chisq", TS=TRUE, model.family="binomial") test2$table test2$NR.report ################################################### ### code chunk number 16: IntroductionIndividualDataFurtherExamples.rnw:266-274 ################################################### inv_wt <- runif(nrow(Wage3), 0, 1) Wage_wt <- cbind(Wage3, inv_wt) test3 <- apc.indiv.model.table(Wage_wt, dep.var="hasdegree", covariates="logwage", test="Wald", dist="Chisq", model.family="binomial", wt.var="inv_wt") test3$table ################################################### ### code chunk number 17: IntroductionIndividualDataFurtherExamples.rnw:282-293 ################################################### library("AER") data("PSID7682") period <- as.numeric(PSID7682$year) + 1975 entry <- period - PSID7682$experience logwage <- log(PSID7682$wage) inunion <- ifelse(PSID7682$union == "yes", 1, 0) insouth <- ifelse(PSID7682$south == "yes", 1, 0) psid2 <- cbind(PSID7682, period, entry, logwage, inunion, insouth) names(psid2)[names(psid2) %in% c("experience", "entry")] <- c("age", "cohort") psid3 <- psid2[psid2$cohort >=1939, ] ################################################### ### code chunk number 18: IntroductionIndividualDataFurtherExamples.rnw:297-303 ################################################### test4 <- apc.indiv.model.table(psid3, dep.var="logwage", covariates = "insouth", plmmodel="random", id.var="id", model.family="gaussian", test="Wald", dist="Chisq") test4$table ################################################### ### code chunk number 19: IntroductionIndividualDataFurtherExamples.rnw:307-312 ################################################### test5 <- apc.indiv.model.table(psid3, dep.var="logwage", plmmodel="within", id.var="id", model.family="gaussian", test="Wald", dist="Chisq") test5$table ################################################### ### code chunk number 20: IntroductionIndividualDataFurtherExamples.rnw:326-337 ################################################### library("ISLR") data("Wage") Wage2 <- Wage[Wage$age >= 25 & Wage$age <= 55, ] names(Wage2)[names(Wage2) %in% c("year","age")] <- c("period","age") cohort <- Wage2$period - Wage2$age indust_job <- ifelse(Wage2$jobclass=="1. Industrial", 1, 0) hasdegree <- ifelse(Wage2$education %in% c("4. College Grad", "5. Advanced Degree"), 1, 0) married <- ifelse(Wage2$maritl == "2. Married", 1, 0) Wage3 <- cbind(Wage2, cohort, indust_job, hasdegree, married) rm(Wage, Wage2, cohort, indust_job, hasdegree, married) ################################################### ### code chunk number 21: IntroductionIndividualDataFurtherExamples.rnw:341-346 ################################################### test1 <- apc.indiv.compare.direct(Wage3, big.model="AP", small.model="tP", dep.var="logwage", model.family="gaussian", test="Wald", dist="F") test1 ################################################### ### code chunk number 22: IntroductionIndividualDataFurtherExamples.rnw:350-355 ################################################### test2 <- apc.indiv.compare.direct(Wage3, big.model="TS", small.model="PC", dep.var="married", covariates="hasdegree", model.family="binomial", test="LR", dist="Chisq") test2[1:8] ################################################### ### code chunk number 23: IntroductionIndividualDataFurtherExamples.rnw:360-369 ################################################### inv_wt <- runif(nrow(Wage3), 0, 1) Wage_wt <- cbind(Wage3, inv_wt) test3 <- apc.indiv.compare.direct(Wage_wt, big.model="APC", small.model="P", dep.var="logwage", covariates = c("hasdegree", "married"), wt.var="inv_wt", test="Wald", dist="Chisq", model.family="gaussian") test3 ################################################### ### code chunk number 24: IntroductionIndividualDataFurtherExamples.rnw:377-388 ################################################### library("AER") data("PSID7682") period <- as.numeric(PSID7682$year) + 1975 entry <- period - PSID7682$experience logwage <- log(PSID7682$wage) inunion <- ifelse(PSID7682$union == "yes", 1, 0) insouth <- ifelse(PSID7682$south == "yes", 1, 0) psid2 <- cbind(PSID7682, period, entry, logwage, inunion, insouth) names(psid2)[names(psid2) %in% c("experience", "entry")] <- c("age", "cohort") psid3 <- psid2[psid2$cohort >=1939, ] ################################################### ### code chunk number 25: IntroductionIndividualDataFurtherExamples.rnw:392-398 ################################################### test4 <- apc.indiv.compare.direct(psid3, big.model="Pd", small.model="t", dep.var="logwage", covariates="insouth", plmmodel="random", id.var="id", model.family="gaussian", test="Wald", dist="F") test4 ################################################### ### code chunk number 26: IntroductionIndividualDataFurtherExamples.rnw:402-409 ################################################### test5 <- apc.indiv.compare.direct(psid3, big.model="FAP", small.model="FP", dep.var="logwage", plmmodel="within", id.var="id", model.family="gaussian", test="Wald", dist="Chisq") test5 ################################################### ### code chunk number 27: IntroductionIndividualDataFurtherExamples.rnw:419-430 ################################################### library("ISLR") data("Wage") Wage2 <- Wage[Wage$age >= 25 & Wage$age <= 55, ] names(Wage2)[names(Wage2) %in% c("year","age")] <- c("period","age") cohort <- Wage2$period - Wage2$age indust_job <- ifelse(Wage2$jobclass=="1. Industrial", 1, 0) hasdegree <- ifelse(Wage2$education %in% c("4. College Grad", "5. Advanced Degree"), 1, 0) married <- ifelse(Wage2$maritl == "2. Married", 1, 0) Wage3 <- cbind(Wage2, cohort, indust_job, hasdegree, married) rm(Wage, Wage2, cohort, indust_job, hasdegree, married) ################################################### ### code chunk number 28: IntroductionIndividualDataFurtherExamples.rnw:434-438 ################################################### library("plyr") library("apc") model1 <- apc.indiv.est.model(Wage3, dep.var="logwage") apc.plot.fit(model1)