heplots (version 1.3-8)

# NLSY: National Longitudinal Survey of Youth Data

## Description

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

## Usage

`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.

## Examples

```# NOT RUN {
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]))

# }
```