mmcsd: Fit fixed and random effects longitudinal model.

In Mmcsd: Modeling Complex Longitudinal Data in a Quick and Easy Way

Fit fixed and random effects longitudinal model.

Description

Estimate the fixed effects of the model, also known as B parameters of the regression,taking into account the sampling plan of the research, and also estimating the covariance matrix of the model considering the estimates of B

Usage

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

Arguments

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

Value

The fit model with class 'mmcsd'.

Examples

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

Mmcsd documentation built on March 31, 2023, 7:23 p.m.