test.mono.mean.bs {statpsych}

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

Description

Computes simultaneous confidence intervals for all adjacent pairwise comparisons of population means using estimated group means, estimated group standard deviations, and samples sizes as input. Equal variances are not assumed. A Satterthwaite adjustment to the degrees of freedom is used to improve the accuracy of the confidence intervals. If one or more lower limits are greater than 0 and no upper limit is less than 0, then conclude that the population means 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 means 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.

Usage

test.mono.mean.bs(alpha, m, sd, n)

Arguments

alpha

alpha level for simultaneous 1-alpha confidence

m

vector of estimated group means

sd

vector of estimated group standard deviations

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 mean difference

• SE - standard error

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

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

Examples

m <- c(12.86, 24.57, 36.29, 53.21)
sd <- c(13.185, 12.995, 14.773, 15.145)
n <- c(20, 20, 20, 20)
test.mono.mean.bs(.05, m, sd, n)

# Should return:
#     Estimate       SE        LL         UL
# 1 2   -11.71 4.139530 -22.07803 -1.3419744
# 2 3   -11.72 4.399497 -22.74731 -0.6926939
# 3 4   -16.92 4.730817 -28.76921 -5.0707936