diet {lcca}R Documentation

Simulated dieting study

Description

This dataset represents a simulated observational study to assess the effect of dieting on emotional distress among adolescent girls. This sample was drawn from an artificial population of one million girls described by Schafer and Kang (2008).

Variables in this population resemble actual variables from the first two waves of the National Longitudinal Study of Adolescent Health (Add Health) (Udry, 2003). However, no actual data from any Add Health participant appears in the population or in the sample; all data were randomly generated from probability distributions as described by Schafer and Kang (2008).

Usage

diet

Format

a data frame with 6,000 rows and 17 variables:

DISTRESS.1

Emotional distress score at Wave I

BLACK

1=Black, 0=otherwise

NBHISP

1=non-Black Hispanic, 0=otherwise

GRADE

Grade in school at Wave I (7, ..., 11)

SLFHLTH

Self-rating of overall health (1=excellent, 2=very good, 3=good, 4=fair, 5=poor)

SLFWGHT

Self-rating of weight (1=very underweight, 2=slightly under, 3=about right, 4=slightly over, 5=very over)

WORKHARD

“When you get what you want, it's usually because you worked hard for it” (1=strongly agree, ..., 5=strongly disagree)

GOODQUAL

“You have lots of good qualities” (1=strongly agree, ..., 5=strongly disagree)

PHYSFIT

“You are physically fit” (1=strongly agree, ..., 5=strongly disagree)

PROUD

“You have a lot to be proud of” (1=strongly agree, ..., 5=strongly disagree)

LIKESLF

“You like yourself just the way you are” (1=strongly agree, ..., 5=strongly disagree)

ACCEPTED

“You feel socially accepted” (1=strongly agree, ..., 5=strongly disagree)

FEELLOVD

“You feel loved and wanted” (1=strongly agree, ..., 5=strongly disagree)

DISTRESS.2

emotional distress score at Wave II

U.1

first binary indicator related to dieting

U.2

second binary indicator related to dieting

U.3

third binary indicator related to dieting

Details

Dieters and nondieters comprise about 20% and 80% of the population, respectively. The treatment variable, a binary indicator of dieting at Wave I, was removed from the dataset and replaced by three conditionally independent binary indicators (U.1, U.2, U.3) with endorsement probabilities of 0.90, 0.85 and 0.80 for dieters and 0.10, 0.15 and 0.20 for nondieters. This structure can be seen by fitting a latent class model with two classes to U.1, U.2, and U.3.

The response variable, DISTRESS.2, is a simulated measure of emotional distress at Wave II.

The remaining variables represent confounders recorded at Wave I which influence girls' emotional distress and their propensities to diet. Adjusting for these confounders is essential for estimating causal effects of dieting on emotional distress. In particular, it is essential to control for DISTRESS.1, because this measure is strongly related to dieting and to DISTRESS.2.

The true causal effects in this population are very small. Dieting versus nondieting increases emotional distress by an average of 0.00253 for the entire population, by -0.02233 for dieters, and by 0.00859 for nondieters.

Source

Schafer, J.L. and Kang, J.D.Y. (2008) Average causal effects from observational studies: a practical guide and simulated example. Psychological Methods, 13, 279-313.

Udry, J.R. (2003) The National Longitudinal Study of Adolescent Health (Add Health), Waves I and II, 1994-1996; Wave III, 2001-2002 (machine-readable data file and documentation), Chapel Hill, NC: Carolina Population Center, University of North Carolina at Chapel Hill.

References

For example analyses of this dataset using functions in the LCCA package, see the manual LCCA Package for R, Version 1 in the subdirectory doc.


[Package lcca version 2.0.0 Index]