statpsych (version 2.0.0)

ci.2x2.prop.bs: 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 effect 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 f = [ f11, f12, f21, f22 ], and the input vector of sample sizes is n = [ n11, n12, n21, n22 ] where the first subscript represents the levels of Factor A and the second subscript represents the levels of Factor B.

For more details, see Section 2.14 of Bonett (2021, Volume 3)

Usage

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

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

• p - two-sided p-value

• LL - lower limit of the adjusted Wald confidence interval

• UL - upper limit of the adjusted Wald confidence interval

Arguments

alpha

alpha level for 1-alpha confidence

f

vector of frequency counts of participants who have the attribute

n

vector of sample sizes

References

Bonett2021statpsych

Price2004statpsych

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 -2.0048 0.04498 -0.54287780 -0.00614181
# A:       -0.11764706 0.06846248 -1.7184 0.08572 -0.25183106  0.01653694
# B:       -0.03921569 0.06846248 -0.5728 0.56678 -0.17339968  0.09496831
# A at b1: -0.25000000 0.09402223 -2.6589 0.00784 -0.43428019 -0.06571981
# A at b2:  0.01923077 0.09787658  0.1965 0.84423 -0.17260380  0.21106534
# B at a1: -0.17307692 0.09432431 -1.8349 0.06652 -0.35794917  0.01179533
# B at a2:  0.09615385 0.09758550  0.9853 0.32446 -0.09511021  0.28741790