nyts18 {glca} | R Documentation |
National Youth Tobacco Survey (NYTS) 2018
Description
This dataset includes 5 manifest items about abortion and several covariates. From the original 2018 National Youth Tobacco Survey data, the Non Hispanic, white students are selected and schools with 30-50 students were selected. Thus, the dataset has 1743 respondents. The covariates include the sex of the respondents and the school ID to which the respondnets belong, and the level of the corresponding school.
Format
A data frame with 1734 observations on the following 8 variables.
ECIGT
Whether to have tried cigarette smoking, even one or two puffs
ECIGAR
Whether to have ever tried cigar smoking, even one or two puffs
ESLT
Whether to have used chewing tobacco, snuff, or dip
EELCIGT
Whether to have used electronic cigarettes or e-cigarettes
EHOOKAH
Whether to have tried smoking tobacco from a hookah or a waterpipe
SEX
Respondent's Sex
SCH_ID
School ID to which the respondent belongs
SCH_LEV
Level of the corresponding school
Source
https://www.cdc.gov/tobacco/data_statistics/surveys/nyts/index.htm
Examples
data("nyts18")
# Model 1: LCA
lca = glca(item(ECIGT, ECIGAR, ESLT, EELCIGT, EHOOKAH) ~ 1,
data = nyts18, nclass = 3)
summary(lca)
# Model 2: LCR
lca = glca(item(ECIGT, ECIGAR, ESLT, EELCIGT, EHOOKAH) ~ SEX,
data = nyts18, nclass = 3)
summary(lca)
coef(lca)
# Model 3: MGLCA
mglca = glca(item(ECIGT, ECIGAR, ESLT, EELCIGT, EHOOKAH) ~ 1,
group = SEX, data = nyts18, nclass = 3)
summary(mglca)
# Model 4: MLCA
mlca = glca(item(ECIGT, ECIGAR, ESLT, EELCIGT, EHOOKAH) ~ 1,
group = SCH_ID, data = nyts18, nclass = 3, ncluster = 2)
summary(mlca)
# Model 5: MLCA with level-1 covariate(s) only
mlcr = glca(item(ECIGT, ECIGAR, ESLT, EELCIGT, EHOOKAH) ~ SEX,
group = SCH_ID, data = nyts18, nclass = 3, ncluster = 2)
summary(mlcr)
coef(mlcr)
# Model 6: MLCA with level-1 and level-2 covariate(s)
# (SEX: level-1 covariate, PARTY: level-2 covariate)
mlcr2 = glca(item(ECIGT, ECIGAR, ESLT, EELCIGT, EHOOKAH) ~ SEX + SCH_LEV,
group = SCH_ID, data = nyts18, nclass = 3, ncluster = 2)
summary(mlcr2)
coef(mlcr2)