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Prepare input data to run the Stan model. Creates / calculates all the required inputs as required by the data{} block of the MMRM Stan program.

Usage

prepare_stan_data(ddat, subjid, visit, outcome, group)

Arguments

ddat

A design matrix

subjid

Character vector containing the subjects IDs.

visit

Vector containing the visits.

outcome

Numeric vector containing the outcome variable.

group

Vector containing the group variable.

Value

A stan_data object. A named list as per data{} block of the related Stan file. In particular it returns:

  • N - The number of rows in the design matrix

  • P - The number of columns in the design matrix

  • G - The number of distinct covariance matrix groups (i.e. length(unique(group)))

  • n_visit - The number of unique outcome visits

  • n_pat - The total number of pattern groups (as defined by missingness patterns & covariance group)

  • pat_G - Index for which Sigma each pattern group should use

  • pat_n_pt - number of patients within each pattern group

  • pat_n_visit - number of non-missing visits in each pattern group

  • pat_sigma_index - rows/cols from Sigma to subset on for the pattern group (padded by 0's)

  • y - The outcome variable

  • Q - design matrix (after QR decomposition)

  • R - R matrix from the QR decomposition of the design matrix

Details

  • The group argument determines which covariance matrix group the subject belongs to. If you want all subjects to use a shared covariance matrix then set group to "1" for everyone.