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)`

- 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.

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.

```
# 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
```