Test of monotonic trend in proportions for an ordered between-subjects factor

Source: R/statpsych3.R

Computes simultaneous confidence intervals for all adjacent pairwise comparisons of population proportions using group frequency counts and samples sizes as input. If one or more lower limits are greater than 0 and no upper limit is less than 0, then conclude that the population proportions are monotonic decreasing. If one or more upper limits are less than 0 and no lower limits are greater than 0, then conclude that the population proportions are monotonic increasing. Reject the hypothesis of a monotonic trend if any lower limit is greater than 0 and any upper limit is less than 0.

test.mono.prop.bs(alpha, f, n)

Arguments

alpha

alpha level for simultaneous 1-alpha confidence

f

vector of frequency counts of participants who have the attribute

n

vector of sample sizes

Value

Returns a matrix with the number of rows equal to the number of adjacent pairwise comparisons. The columns are:

  • Estimate - estimated proportion difference

  • SE - standard error

  • LL - one-sided lower limit of the confidence interval

  • UL - one-sided upper limit of the confidence interval

Examples

f <- c(67, 49, 30, 10)
n <- c(100, 100, 100, 100)
test.mono.prop.bs(.05, f, n)
#>       Estimate         SE         LL        UL
#>  1 2 0.1764706 0.06803446 0.01359747 0.3393437
#>  2 3 0.1862745 0.06726135 0.02525219 0.3472968
#>  3 4 0.1960784 0.05493010 0.06457688 0.3275800

# Should return:
#      Estimate         SE         LL        UL
# 1 2 0.1764706 0.06803446 0.01359747 0.3393437
# 2 3 0.1862745 0.06726135 0.02525219 0.3472968
# 3 4 0.1960784 0.05493010 0.06457688 0.3275800