Bivariate analysis for 2 groups for paired data

Automatic paired test for continuous variables for 2 groups. Variable names can be assigned using table1::label() function.

Usage

continuous_2g_pair(
  data,
  groupvar,
  ttest_args = list(),
  wilcox_args = list(),
  flextableformat = TRUE
)

Arguments

data

Data frame from which variables will be extracted.

groupvar

Grouping variable. Must have exactly 2 levels.

ttest_args

Arguments to be passed to t.test() function.

wilcox_args

Arguments to be passed to wilcox.test() function.

flextableformat

Logical operator to indicate the output desired. Default is TRUE. When FALSE, function will return a dataframe format.

Value

A dataframe or flextable with containing p values for paired tests along with statistics for normality and homocedasticity.

Examples

data <- data.frame(group = rep(letters[1:2], 30),
                   var1 = rnorm(60, mean = 15, sd = 5),
                  var2 = rnorm(60, mean = 20, sd = 2),
                  var3 = rnorm(60, mean = 10, sd = 1),
                  var4 = rnorm(60, mean = 5, sd =2))
data$group<-as.factor(data$group)

continuous_2g_pair(data = data, groupvar = "group")
Variable
P_Shapiro_Resid
P_T_Paired
P_Wilcoxon
Diff_Means
CI_Lower
CI_Upper
var1
0.84
0.93
0.81
-0.11
-2.68117
2.45169
var2
0.26
0.10
0.16
-0.75
-1.63535
0.14264
var3
0.90
0.75
0.92
-0.10
-0.70178
0.50859
var4
0.46
0.37
0.40
0.34
-0.43403
1.11921

# Set names to variables
if(requireNamespace("table1")){
table1::label(data$var1) <- "Variable 1"
table1::label(data$var2) <- "Variable 2"
table1::label(data$var3) <- "Variable 3"
table1::label(data$var4) <- "Variable 4"

continuous_2g_pair(data = data, groupvar = "group", flextableformat = FALSE)
}
#>     Variable P_Shapiro_Resid P_T_Paired P_Wilcoxon Diff_Means CI_Lower CI_Upper
#> 1 Variable 1         0.84323    0.92777    0.80783   -0.11474 -2.68117  2.45169
#> 2 Variable 2         0.26211    0.09663    0.15795   -0.74636 -1.63535  0.14264
#> 3 Variable 3         0.89681    0.74644    0.91930   -0.09659 -0.70178  0.50859
#> 4 Variable 4         0.45718    0.37438    0.40449    0.34259 -0.43403  1.11921