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Confidence interval for a linear contrast of regression coefficients in multiple group regression model

Source: R/statpsych2.R
ci.lc.reg.Rd

Computes a confidence interval and test statistic for a linear contrast of population regression coefficients (e.g., a y-intercept or a slope coefficient) across groups in a multiple group regression model. Equality of error variances across groups is not assumed. A Satterthwaite adjustment to the degrees of freedom is used to improve the accuracy of the confidence interval.

For more details, see Section 2.20 of Bonett (2021, Volume 2)

Usage

ci.lc.reg(alpha, est, se, n, s, v)

Arguments

alpha

alpha level for 1-alpha confidence

est

vector of parameter estimates

se

vector of standard errors

n

vector of group sample sizes

s

number of predictor variables for each within-group model

v

vector of contrast coefficients

Value

Returns a 1-row matrix. The columns are:

  • Estimate - estimated linear contrast

  • SE - standard error

  • t - t test statistic

  • df - degrees of freedom

  • p - two-sided p-value

  • LL - lower limit of the confidence interval

  • UL - upper limit of the confidence interval

References

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

Examples

est <- c(1.74, 1.83, 0.482)
se <- c(.483, .421, .395)
n <- c(40, 40, 40)
v <- c(.5, .5, -1)
ci.lc.reg(.05, est, se, n, 4, v)
#>  Estimate        SE     t      df       p        LL       UL
#>     1.303 0.5085838 2.562 78.8197 0.01231 0.2906532 2.315347

# Should return:
# Estimate        SE      t      df       p        LL       UL
#    1.303 0.5085838 2.5620 78.8197 0.01231 0.2906532 2.315347