sensitivity.bayes.splines.fit: sensitivity.bayes.splines.fit

In kreidles/informativeDropout: informativeDropout: varying coefficient models to account for informative dropout

Description

Sensitivity analysis for models using the 'bayes.splines' model Allows users to determine how sensitive the results are if the true slope after dropout changes.

Usage

## S3 method for class 'bayes.splines.fit'
sensitivity(fit, times.estimation, deltas,
  data.onePerSubject, times.dropout.var, group.var = NULL,
  covariates.time.var = NULL, covariates.nontime.var = NULL)

Arguments

fit	the fit object from a call to informativeDropout, using the 'bayes.splines' model
times.estimation	vector of times at which to estimate the expected value of the outcome
deltas	vector of multipliers to increase/decrease slope after dropout
data.onePerSubject	data frame containing one row per participant. The data frame must include dropout time and grouping variable (if multi-group design). Both time- and non-time-interacted covariates should be specified if the user wishes to include them in the sensitivity analysis.
times.dropout.var	column name containing drop out times
group.var	column name containing group values
covariates.time.var	vector of columns containing time-interacted covariates
covariates.nontime.var	vector of columns containing non-time-interacted covariates

kreidles/informativeDropout documentation built on Sept. 13, 2020, 12:15 a.m.