NLSY: National Longitudinal Survey of Youth Data In heplots: Visualizing Hypothesis Tests in Multivariate Linear Models

Description

The dataset come from a small random sample of the U.S. National Longitudinal Survey of Youth.

Usage

 `1` ```data(NLSY) ```

Format

A data frame with 243 observations on the following 6 variables.

`math`

Math achievement test score

`read`

`antisoc`

score on a measure of child's antisocial behavior, `0:6`

`hyperact`

score on a measure of child's hyperactive behavior, `0:5`

`income`

yearly income of child's father

`educ`

years of education of child's father

Details

In this dataset, `math` and `read` scores are taken at the outcome variables. Among the remaining predictors, `income` and `educ` might be considered as background variables necessary to control for. Interest might then be focused on whether the behavioural variables `antisoc` and `hyperact` contribute beyond that.

Source

This dataset was derived from a larger one used by Patrick Curran at the 1997 meeting of the Society for Research on Child Development (SRCD). A description now only exists on the WayBack Machine, http://web.archive.org/web/20050404145001/http://www.unc.edu/~curran/example.html.

More details are available at http://web.archive.org/web/20060830061414/http://www.unc.edu/~curran/srcd-docs/srcdmeth.pdf.

Examples

 ``` 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``` ```data(NLSY) #examine the data scatterplotMatrix(NLSY, smooth=FALSE) # test control variables by themselves # ------------------------------------- mod1 <- lm(cbind(read,math) ~ income+educ, data=NLSY) Anova(mod1) heplot(mod1, fill=TRUE) # test of overall regression coefs <- rownames(coef(mod1))[-1] linearHypothesis(mod1, coefs) heplot(mod1, fill=TRUE, hypotheses=list("Overall"=coefs)) # additional contribution of antisoc + hyperact over income + educ # ---------------------------------------------------------------- mod2 <- lm(cbind(read,math) ~ antisoc + hyperact + income + educ, data=NLSY) Anova(mod2) coefs <- rownames(coef(mod2))[-1] heplot(mod2, fill=TRUE, hypotheses=list("Overall"=coefs, "mod2|mod1"=coefs[1:2])) linearHypothesis(mod2, coefs[1:2]) heplot(mod2, fill=TRUE, hypotheses=list("mod2|mod1"=coefs[1:2])) ```

heplots documentation built on Oct. 7, 2021, 1:07 a.m.