Test for Trend in Proportions

Performs chi-squared test for trend in proportion. This test is also known as Cochran-Armitage trend test.

Wrappers around the R base function prop.trend.test() but returns a data frame for easy data visualization.

prop_trend_test(xtab, score = NULL)

Arguments

xtab

a cross-tabulation (or contingency table) with two columns and multiple rows (rx2 design). The columns give the counts of successes and failures respectively.

score

group score. If NULL, the default is group number.

Value

return a data frame with some the following columns:

• n: the number of participants.

• statistic: the value of Chi-squared trend test statistic.

• df: the degrees of freedom.

• p: p-value.

• method: the used statistical test.

• p.signif: the significance level of p-values and adjusted p-values, respectively.

The returned object has an attribute called args, which is a list holding the test arguments.

Examples

# Proportion of renal stone (calculi) across age
#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# Data
xtab <- as.table(rbind(
  c(384, 536, 335),
  c(951, 869, 438)
))
dimnames(xtab) <- list(
  stone = c("yes", "no"),
  age = c("30-39", "40-49", "50-59")
)
xtab
#>      age
#> stone 30-39 40-49 50-59
#>   yes   384   536   335
#>   no    951   869   438
# Compare the proportion of survived between groups
prop_trend_test(xtab)
#> # A tibble: 1 × 6
#>       n statistic        p p.signif    df method               
#> * <dbl>     <dbl>    <dbl> <chr>    <dbl> <chr>                
#> 1  3513      49.7 1.78e-12 ****         1 Chi-square trend test