glca (version 0.1.0)

nhanes: National Health and Nutrition Examination Survey 2015-2016

Description

There is a 9 manifest items about frequency of depression symptoms over the past 2 weeks from National Health and Nutrition Examination Survey (NHANES). All of 9 items are measured 4 point-scale, "Not at all", "Several days", "More than half the days", and "Nearly every day". Those four categories are converted to binary as "Yes" ("Nearly every day", "More than half the days", "Several days") and "No" ("Not at all"). The dataset includes gender, age, and race of respondents as covariates.

Format

A data frame with 5735 observations on the following 8 variables.

DPQ010

Have little interest in doing things

DPQ020

Feeling down, depressed, or hopeless

DPQ030

Trouble sleeping or sleeping too much

DPQ040

Feeling tired or having little energy

DPQ050

Poor appetite or overeating

DPQ060

Feeling bad about yourself

DPQ070

Trouble concentrating on things

DPQ080

Moving or speaking slowly or too fast

DPQ090

Thought you would be better off dead

AGE

Age in years at screening

GENDER

Respondent's Gender

RACE

Race/Hispanic origin w/ NH Asian

References

Centers for Disease Control and Prevention (CDC). National Center for Health Statistics (NCHS). National Health and Nutrition Examination Survey Data. Hyattsville, MD: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, [2015-2016][https://wwwn.cdc.gov/nchs/nhanes/ContinuousNhanes/Default.aspx?BeginYear=2015]

Examples

# NOT RUN {
data("nhanes")
# Model 1: LCA
lca = glca(item(starts.with = "DPQ") ~ 1, data = nhanes, nclass = 2)
summary(lca)

# Model 2: LCA with covariate(s)
lcr = glca(item(starts.with = "DPQ") ~ AGE, data = nhanes, nclass = 3)
summary(lcr)
coef(lcr)

# Model 3: MGLCA
mglca = glca(item(starts.with = "DPQ") ~ 1, group = GENDER,
             data = nhanes, nclass = 3)
summary(mglca)

# Model 4: MGLCA with covariate(s)
mglcr = glca(item(starts.with = "DPQ") ~ AGE, group = GENDER,
             data = nhanes, nclass = 3)
summary(mglcr)
coef(mglcr)

# Model 5: MLCA
mlca = glca(item(starts.with = "DPQ") ~ 1, group = RACE,
            data = nhanes, nclass = 3, ncluster = 2)
summary(mlca)
# }