MarihuanaAlcohol {cmm} | R Documentation |

## Marihuana and alcohol use during adolescence, five-wave panel

### Description

Panel study with five time points. A group of 269 youths were interviewed at ages 13, 14, 15, 16, and 17, and asked (among other things) about their marijuana and alcohol use (Eliot, Huizinga & Menard, 1989). The data are tabulated in Bergsma, Croon, and Hagenaars (2009, p. 128). 208 observations do not have missing values.

Sections 4.2 and 4.4 in Bergsma, Croon, and Hagenaars (2009).

### Usage

`data(MarihuanaAlcohol)`

### Format

A data frame with 269 observations on the following variables.

`Gender`

(factor): 1 = Male; 2 = Female.

`M1`

Use of marihuana at time 1 (ordered): 1 = Never; 2 = Occasionally; 3 = Frequently.

`M2`

Use of marihuana at time 2 (ordered): see

`M1`

.

`M3`

Use of marihuana at time 3 (ordered): see

`M1`

.

`M4`

Use of marihuana at time 4 (ordered): see

`M1`

.

`M5`

Use of marihuana at time 5 (ordered): see

`M1`

.

`A1`

Use of alcohol at time 1 (ordered): see

`M1`

.

`A2`

Use of alcohol at time 2 (ordered): see

`M1`

.

`A3`

Use of alcohol at time 3 (ordered): see

`M1`

.

`A4`

Use of alcohol at time 4 (ordered): see

`M1`

.

`A5`

Use of alcohol at time 5 (ordered): see

`M1`

.

### Source

US National Youth Survey (NYS): teenage marijuana and alcohol use (Elliot, Huizinga and Menard, 1989)

### References

Bergsma, W. P., Croon, M. A., & Hagenaars, J. A. P. (2009).
*Marginal models for dependent, clustered, and longitudinal categorical data.*
New York: Springer.

Elliot, D. S., Huizinga, D. & Menard, S. (1989). Multiple problem youth: Delinquency, substance use, and metal health problems. New York: Springer.

### Examples

```
data(MarihuanaAlcohol)
# Table MA: marginal loglinear analysis (BCH Section 4.2.1)
# listwise deletion of missing values and deletion of Gender and Alcohol use
dat <- MarihuanaAlcohol[-row(MarihuanaAlcohol)[is.na(MarihuanaAlcohol)],2:6]
# at yields the vectorized 5x3 table MA (marijuana use x age)
at <- MarginalMatrix(var = c("M1", "M2", "M3", "M4", "M5"),
marg = list(c("M1"), c("M2"), c("M3"), c("M4"), c("M5")),
dim = c(3, 3, 3, 3, 3))
obscoeff <- SampleStatistics(dat = dat,
coeff = list("log", at),
CoefficientDimensions = c(5,3),
Labels = c("Age", "M"),
ShowCoefficients = FALSE,
ShowParameters = TRUE)
```

*cmm*version 1.0 Index]