Design and analysis: a researcher's handbook
The fourth edition of Design and Analysis continues to offer a readily accessible introduction to the designed experiment in research and the statistical analysis of the data from such experiments. Unique because it emphasizes the use of analytical procedures, this book is appropriate for all as it requires knowledge of only the most fundamental mathematical skills and little or no formal statistical background. Topics include: single- and two-factor designs with independent groups of subjects; corresponding designs with multiple observations; analysis of designs with unequal sample sizes; analysis of covariance; designs with three factors, including all combinations of between-subjects and within-subject factors; random factors and statistical generalization; and nested factors. This book lives up to its name as a handbook, because of its usefulness as a source and guide to researchers who require assistance in both planning a study and analyzing its results.
82 pages matching within-subjects design in this book
Results 1-3 of 82
What people are saying - Write a review
We haven't found any reviews in the usual places.
The Sensitivity of an Experiment
28 other sections not shown
A X B interaction ABC matrix analysis of variance assumptions average B X S basic ratios calculate Chapter coefﬁcients column combined comp comparison matrix completely randomized completely randomized design component computational formulas consider deﬁned degrees of freedom deviation df MS F effect of factor equal error variance estimate expected value experimental design F distribution F ratio F test factorial design factorial experiment ﬁnd ﬁndings ﬁrst independent variables inﬂuence interaction comparisons Latin square analysis levels of factor linear main effect ment MSS/A nested factor null hypothesis number of subjects obtained partial factorial particular planned comparisons practice effects presented problem procedures randomly reﬂect repeated factor represent signiﬁcant simple effects single-df comparisons single-factor design single-factor experiment sources of variance speciﬁcally sums of squares Table three-way interaction tion treatment conditions treatment effects treatment means trend two-way type I error unequal sample sizes within-groups mean square within-subjects design