ci.c.ancova {MBESS} | R Documentation |
To calculate the confidence interval for an unstandardized contrast in the one-covariate ANCOVA.
ci.c.ancova(Psi, means, error.var.ancova = NULL, c.weights, n, x.bar, SSwithin.x, conf.level = 0.95, ...)
Psi |
the unstandardized contrast of adjusted means |
means |
the vector that contains the adjusted mean of each group |
error.var.ancova |
the error variance obtained from the ANCOVA summary table; i.e., mean square within in the ANCOVA table |
c.weights |
the contrast weights |
n |
either a single number that indicates the sample size per group, or a vector that contains the sample size of each group |
x.bar |
a vector that contains the group means of the covariate |
SSwithin.x |
the sum of squares within groups obtained from the summary table for ANOVA on the covariate |
conf.level |
the desired confidence interval coverage, (i.e., 1 - Type I error rate) |
... |
allows one to potentially include parameter values for inner functions |
lower.limit |
the lower confidence limit of the (unstandardized) ANCOVA contrast |
lower.limit |
the upper confidence limit of the (unstandardized) ANCOVA contrast |
Be sure to use the error varaince and not its square root (i.e., the standard deviation of the errors).
If n
receives a single number, that number is considered as the sample size per group. If n
receives a vector, the vector is considered as the sample size of each group.
Be sure to use fractions not the integers to specify c.weights
. For exmaple, in an ANCOVA of four groups,
if the user wants to compare the mean of group 1 and 2 with the mean of group 3 and 4, c.weights
should
be specified as c(0.5, 0.5, -0.5, -0.5) rather than c(1, 1, -1, -1). Make sure the sum of the contrast weights
are zero.
Keke Lai (University of Notre Dame; Lai.15@ND.Edu)
Kelley, K. (2007). Constructing confidence intervals for standardized effect sizes: Theory, application, and implementation. Journal of Statistical Software, 20 (8), 1-24.
Maxwell, S. E., & Delaney, H. D. (2004). Designing experiments and analyzing data: A model comparison perspective. Mahwah, NJ: Erlbaum.
ci.c
, ci.sc.ancova
# Maxwell & Delaney (2004, pp. 428-468) offer an example that 30 depressive # individuals are randomly assigned to three groups, 10 in each, and ANCOVA # is performed on the posttest scores using the participants' pretest # scores as the covariate. The means of pretest scores of group 1 to 3 are # 17, 17,7, and 17,4, respectively, and the adjusted means of groups 1 to 3 # are 7.5, 12, and 14, respectively. The error variance in ANCOVA is 29, # and the sum of squares within groups from ANOVA on the covariate is # 313.37. # To obtained the confidence interval for adjusted mean of group 1 versus # group 2: ci.c.ancova(means=c(7.5, 12, 14), error.var.ancova=29, c.weights=c(1, -1, 0), n=10, x.bar=c(17, 17.7, 17.4), SSwithin.x=313.37)