ci.2x2.prop.bs: Computes tests and confidence intervals of effects in a 2x2...

In statpsych: Statistical Methods for Psychologists

Computes tests and confidence intervals of effects in a 2x2 between- subjects design for proportions

Description

Computes adjusted Wald confidence intervals and tests for the AB interaction effect, main effect of A, main efect of B, simple main effects of A, and simple main effects of B in a 2x2 between-subjects factorial design with a dichotomous response variable. The input vector of frequency counts is f11, f12, f21, f22, and the input vector of sample sizes is n11, n12, n21, n22 where the first subscript represents the levels of Factor A and the second subscript represents the levels of Factor B.

Usage

ci.2x2.prop.bs(alpha, f, n)

Arguments

alpha	alpha level for 1-alpha confidence
f	vector of frequency counts of participants with attribute
n	vector of sample sizes

Value

Returns a 7-row matrix (one row per effect). The columns are:

• Estimate - adjusted estimate of effect

• SE - standard error

• z - z test statistic for test of null hypothesis

• p - p-value

• LL - lower limit of the adjusted Wald confidence interval

• UL - upper limit of the adjusted Wald confidence interval

Examples

f = c(15, 24, 28, 23)
n = c(50, 50, 50, 50)
ci.2x2.prop.bs(.05, f, n)

# Should return:
#             Estimate         SE          z           p          LL          UL
# AB:      -0.27450980 0.13692496 -2.0048193 0.044982370 -0.54287780 -0.00614181
# A:       -0.11764706 0.06846248 -1.7184165 0.085720668 -0.25183106  0.01653694
# B:       -0.03921569 0.06846248 -0.5728055 0.566776388 -0.17339968  0.09496831
# A at b1: -0.25000000 0.09402223 -2.6589456 0.007838561 -0.43428019 -0.06571981
# A at b2:  0.01923077 0.09787658  0.1964798 0.844234654 -0.17260380  0.21106534
# B at a1: -0.17307692 0.09432431 -1.8349132 0.066518551 -0.35794917  0.01179533
# B at a2:  0.09615385 0.09758550  0.9853293 0.324462356 -0.09511021  0.28741790

statpsych documentation built on July 9, 2023, 6:50 p.m.