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Scheffe confidence interval for a linear contrast of means in a between-subjects design

Source: R/statpsych1.R
ci.lc.mean.scheffe.Rd

Computes a Scheffe confidence interval for a linear contrast of population means in a between-subjects design. A Scheffe p-value is computed for the test statistic. The Scheffe method assumes equal population variances. This function is useful in exploratory studies where the linear contrast of means was not planned but was suggested by the pattern of sample means. Use the ci.lc.mean.bs function with a Bonferroni adjusted alpha value to compute simultaneous confidence intervals for two or more planned linear contrasts of means.

Usage

ci.lc.mean.scheffe(alpha, m, sd, n, v)

Arguments

alpha

alpha level for 1-alpha confidence

m

vector of estimated group means

sd

vector of estimated group standard deviations

n

vector of sample sizes

v

vector of between-subjects contrast coefficients

Value

Returns a 2-row matrix. The columns are:

  • Estimate - estimated linear contrast

  • SE - standard error

  • t - t test statistic

  • df - degrees of freedom

  • p - two-sided Scheffe p-value

  • LL - lower limit of the Scheffe confidence interval

  • UL - upper limit of the Scheffe confidence interval

References

Snedecor GW, Cochran WG (1989). Statistical Methods, 8th edition. ISU University Pres, Ames, Iowa.

Examples


m <- c(33.5, 37.9, 38.0, 44.1)
sd <- c(3.49, 3.84, 3.65, 4.98)
n <- c(10, 10, 10, 10)
v <- c(.5, .5, -.5, -.5)
ci.lc.mean.scheffe(.05, m, sd, n, v)
#>  Estimate       SE       t       p        LL        UL
#>     -5.35 1.275231 -4.1953 0.00228 -9.089451 -1.610549

# Should return:
#  Estimate       SE       t       p        LL        UL
#     -5.35 1.275231 -4.1953 0.00228 -9.089451 -1.610549