expss (version 0.11.4)

# compare_proportions: Calculate significance (p-values) of differences between proportions/means

## Description

`compare_proportions` calculates p-values (via z-test) for comparison between each proportion in the `prop1` and `prop2`. Results are calculated with the same formula as in prop.test without continuity correction. `compare_means` calculates p-values (via t-test) for comparison between each mean in the `mean1` and `mean2`. Results are calculated on the aggregated statistics (means, std. devs, N) with the same formula as in t.test. These functions mainly intended for usage inside significance_cpct and significance_means.

## Usage

```compare_proportions(prop1, prop2, base1, base2, common_base = 0)compare_means(
mean1,
mean2,
sd1,
sd2,
base1,
base2,
common_base = 0,
var_equal = FALSE
)```

## Value

numeric vector with p-values

## Arguments

prop1

a numeric vector of proportions in the group 1. Values should be between 0 and 1

prop2

a numeric vector of proportions in the group 2. Values should be between 0 and 1

base1

a numeric vector for `compare_means` and single number for `compare_proportions`. Number of valid cases for each mean in the first group for `compare_means` and number of cases for `compare_proportions`.

base2

a numeric vector for `compare_means` and single number for `compare_proportions`. Number of valid cases for each mean in the second group for `compare_means` and number of cases for `compare_proportions`.

common_base

numeric. Number of cases that belong to both values in the first and the second argument. It can occur in the case of overlapping samples. Calculations are made according to algorithm in IBM SPSS Statistics Algorithms v20, p. 263. Note that with these adjustments t-tests between means are made with equal variance assumed (as with ```var_equal = TRUE```).

mean1

a numeric vector of the means in the first group.

mean2

a numeric vector of the means in the second group.

sd1

a numeric vector of the standard deviations in the first group. Values should be non-negative.

sd2

a numeric vector of the standard deviations in the second group. Values should be non-negative.

var_equal

a logical variable indicating whether to treat the variances in the groups as being equal. For details see t.test.

significance_cpct, significance_means, prop.test, t.test

## Examples

Run this code
``````# proportions
data(mtcars)
counts = table(mtcars\$am, mtcars\$vs)
props = prop.table(counts)
compare_proportions(props[,1], props[,2],
colSums(counts)[1], colSums(counts)[1])

# means
t.test(mpg ~ am, data = mtcars)\$p.value
# the same result
with(mtcars,
compare_means(
mean(mpg[am==0]), mean(mpg[am==1]),
sd(mpg[am==0]),  sd(mpg[am==1]),
length(mpg[am==0]), length(mpg[am==1])
))
``````

Run the code above in your browser using DataCamp Workspace