# defMiss: Definitions for missing data In kgoldfeld/simstudy: Simulation of Study Data

## Description

Add single row to definitions table for missing data

## Usage

 ```1 2``` ```defMiss(dtDefs = NULL, varname, formula, logit.link = FALSE, baseline = FALSE, monotonic = FALSE) ```

## Arguments

 `dtDefs` Definition data.table to be modified `varname` Name of variable with missingness `formula` Formula to describe pattern of missingness `logit.link` Indicator set to TRUE when the probability of missingness is based on a logit model. `baseline` Indicator is set to TRUE if the variable is a baseline measure and should be missing throughout an entire observation period. This is applicable to repeated measures/longitudinal data. `monotonic` Indicator set to TRUE if missingness at time t is followed by missingness at all follow-up times > t.

## Value

A data.table named dtName that is an updated data definitions table

`genMiss`, `genObs`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23``` ```def1 <- defData(varname = "m", dist = "binary", formula = .5) def1 <- defData(def1, "u", dist = "binary", formula = .5) def1 <- defData(def1, "x1", dist="normal", formula = "20*m + 20*u", variance = 2) def1 <- defData(def1, "x2", dist="normal", formula = "20*m + 20*u", variance = 2) def1 <- defData(def1, "x3", dist="normal", formula = "20*m + 20*u", variance = 2) dtAct <- genData(1000, def1) defM <- defMiss(varname = "x1", formula = .15, logit.link = FALSE) defM <- defMiss(defM, varname = "x2", formula = ".05 + m * 0.25", logit.link = FALSE) defM <- defMiss(defM, varname = "x3", formula = ".05 + u * 0.25", logit.link = FALSE) defM <- defMiss(defM, varname = "u", formula = 1, logit.link = FALSE) # not observed defM # Generate missing data matrix missMat <- genMiss(dtName = dtAct, missDefs = defM, idvars = "id") missMat # Generate observed data from actual data and missing data matrix dtObs <- genObs(dtAct, missMat, idvars = "id") dtObs ```