Confidence interval for a slope of a proportion in a single-factor experimental design with a quantitative between-subjects factor

Computes a test statistic and an adjusted Wald confidence interval for the population slope of proportions in a one-factor experimental design with a quantitative between-subjects factor.

For more details, see Section 4.4 of Bonett (2021, Volume 3)

Usage

ci.slope.prop.bs(alpha, f, n, x)

Arguments

alpha: alpha level for 1-alpha confidence
f: vector of frequency counts of participants who have the attribute
n: vector of sample sizes
x: vector of quantitative factor values

Value

Returns a 1-row matrix. The columns are:

Estimate - adjusted slope estimate
SE - adjusted 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

References

Price RM, Bonett DG (2004). “An improved confidence interval for a linear function of binomial proportions.” Computational Statistics & Data Analysis, 45(3), 449–456. ISSN 01679473, doi:10.1016/S0167-9473(03)00007-0 .

Bonett DG (2021). Statistical Methods for Psychologists https://dgbonett.sites.ucsc.edu/.

Examples

f <- c(11, 15, 20, 27)
n <- c(60, 60, 60, 60)
x <- c(10, 20, 30, 40)
ci.slope.prop.bs(.05, f, n, x)
#>     Estimate          SE      z       p          LL         UL
#>  0.008688525 0.002566409 3.3855 0.00071 0.003658456 0.01371859

# Should return:
#    Estimate          SE      z       p          LL         UL
# 0.008688525 0.002566409 3.3855 0.00071 0.003658456 0.01371859