# meantab: Tabulate means of covariates after matching In designmatch: Matched Samples that are Balanced and Representative by Design

 meantab R Documentation

## Tabulate means of covariates after matching

### Description

Function for tabulating the means and other basic statistics useful to assess covariate balance after matching.

### Usage

```	meantab(X_mat, t_ind, t_id, c_id, exact = NULL, digits = 2)
```

### Arguments

 `X_mat` matrix of covariates: a matrix of covariates used to assess balance. `t_ind` treatment indicator: a vector of zeros and ones indicating treatment (1 = treated; 0 = control). `t_id` a vector of indexes of the treated units. `c_id` a vector of indexes of the matched controls. `exact` a vector of characters equal to "f" or "w" indicating whether Fisher's exact test or Wilcoxon rank-sum test should be used for binary (or categorical) and continous covariates, respectively. Otherwise, if exact `exact = NULL`, simple t-tests are used. The default is `exact = NULL`. If `exact != NULL`, the length of `exact` has to be equal to the number of columns of `X_mat`. `digits` a scalar indicating the number of digits to display in the columns of the table.

### Details

`meantab` is a function for tabulating the means and other basic statistics useful to assess covariate balance after matching.

### Value

A table with the following columns:

 `Mis` proportion of missing values for each covariate; `Min` minimum value for each covariate; `Max` maximum value for each covariate; `Mean T` mean of the treated units for each covariate; `Mean C` mean of the matched controls for each covariate; `Std Dif` standardized differences in means after matching for each covariate; `P-val` P-values for t-tests for differences in means between treated units and matched controls for each covariate.

### Examples

```	# Load data
data(germancities)

# Sort and attach data
germancities = germancities[order(germancities\$treat, decreasing = TRUE), ]
attach(germancities)

# Treatment indicator
t_ind = treat

# Indexes of the treated units
t_id = which(t_ind == 1)

# Matrix of covariates
X_mat = cbind(log2pop, popgrowth1939, popgrowth3339, emprate, indrate, rubble,
rubblemiss, flats, flatsmiss, refugees)

# Indices of the matched controls (obtained using bmatch in designmatch)
c_id = c(67, 75, 39, 104, 38, 93, 79, 59, 64, 55, 106, 99, 97, 61, 82, 57,
76, 47, 46, 49)

# meantab
meantab(X_mat, t_ind, t_id, c_id)

# meantab
meantab(X_mat, t_ind, t_id, c_id, exact = c(rep("w", 6), "f", "w", "f", "w"), digits = 3)
```

designmatch documentation built on Aug. 26, 2022, 1:07 a.m.