clm: Fit fixed and random effects longitudinal model.
In phmpacheco-ufjf/clm: A package to deal with complex longitudinal survey data

Description Usage Arguments Value Examples

View source: R/clm____main.R

Fit fixed and random effects longitudinal model.

1	clm(formula, waves, ids, weights, stratum, cluster, data, sigma = "identity")

`formula`	A formula
`waves`	a dataframe column or an array
`ids`	a dataframe column or an array
`weights`	a dataframe column or an array
`stratum`	a dataframe column or an array
`cluster`	a dataframe column or an array
`data`	A dataframe or tibble
`sigma`	A character or a square matrix

The fit model with class 'clm'.

fit <- clm(score ~ wave + ageg + ecacg + qualifg,
  waves = wave, ids = id,
  weights = weight, stratum = strata, cluster = cluster,
  data = data, sigma = "exchangeable"
)