ERIC_NO:
ED423303
TITLE:
Comparable Confidence Intervals for Multi-Sample and Replication Studies.
AUTHOR:
Huynh, Cam-Loi
PUBLICATION_DATE:
1998
ABSTRACT:
When the same parameters are estimated by data from several independent samples, it may happen that, for any pair of samples, even though the
test for parameter discrepancy is statistically significant, the two
individual confidence intervals overlap. To overcome this potential
contradiction, a new type of one-sample confidence intervals is developed.
Their evaluation will lead to the same statistical decisions reached by
the two-sample test for parameter discrepancy. Moreover, the simultaneous
decisions on parameter estimation, statistical inference, and directional
prediction can be made with specified confidence coefficients and error
rates by simply comparing a pair of comparable confidence intervals. In
contrast with conventional confidence intervals, the comparable new
confidence intervals have narrower widths, disjoint or overlap depending
on whether the parameter discrepancy is statistically significant or not.
The proposed procedure can be applied to both simple and multiple a-priori
comparisons of means, proportions, and correlation coefficients. Due to
its mathematical simplicity, the method should be valuable for research
practitioners and quite suitable to be taught in courses of research methods
in the behavioral and social sciences. An appendix explains the derivation
of the formulas in Table 1. (Contains 3 tables and 49 references.)
(Author/SLD)
MAJOR_DESCRIPTORS:
Comparative Analysis; Estimation (Mathematics); Research Methodology; Sampling
;
MINOR DESCRIPTORS:
Foreign Countries;
IDENTIFIERS:
*Confidence Intervals (Statistics); *Research Replication
PUBLICATION_TYPE:
142