Experimental Design: Procedures for the Behavioral SciencesThis text provides the graduate student in experimental design with detailed coverage of the designs and techniques having the greatest potential use in behavioural research. The emphasis of the text is on the logical rather than the mathematical basis of experimental design. It explores the relationship between analysis of variance and regression analysis, and describes all of the ANOVA exprimental designs that are potentially useful in the behavioural sciences and education. |
From inside the book
Results 1-3 of 69
Page 164
... model is designated as a random - effects model or model II . - A comparison of the expected values of the mean squares for the two models is given in Table 4.7-1 . The derivation of E ( MS ) is discussed in Section 2.3 . If p is small ...
... model is designated as a random - effects model or model II . - A comparison of the expected values of the mean squares for the two models is given in Table 4.7-1 . The derivation of E ( MS ) is discussed in Section 2.3 . If p is small ...
Page 361
... EFFECTS , MIXED , AND RANDOM - EFFECTS MODELS Random sampling was not used to determine the levels of treatments included in the police attitude experiment described in Section 8.3 . Instead the particular levels were included because ...
... EFFECTS , MIXED , AND RANDOM - EFFECTS MODELS Random sampling was not used to determine the levels of treatments included in the police attitude experiment described in Section 8.3 . Instead the particular levels were included because ...
Page 362
Procedures for the Behavioral Sciences Roger E. Kirk. mixed model ( model III ) . The treatment effects are fixed or random depending on whether they were randomly sampled . Interaction effects are random effects if they involve one or more ...
Procedures for the Behavioral Sciences Roger E. Kirk. mixed model ( model III ) . The treatment effects are fixed or random depending on whether they were randomly sampled . Interaction effects are random effects if they involve one or more ...
Contents
INTRODUCTION TO BASIC CONCEPTS | 1 |
FUNDAMENTAL ASSUMPTIONS | 49 |
Introduction to Multiple Comparison Tests | 90 |
Copyright | |
32 other sections not shown
Other editions - View all
Common terms and phrases
a₁ a₂ ABCD analysis of variance ANOVA b₁ b2 BL(A C₁ cell coefficients completely randomized design components Computational formulas Computational Procedures confounded degrees of freedom denoted dependent variable described in Section difference error rate error term estimate example expected values experiment experimental design model experimental units F ratio F statistic fractional factorial design full rank experimental groups independent interaction Latin square levels of treatment linear matrix mean squares model approach MSRES MSWCELL MSWG nuisance variable null hypothesis observations obtained parameters population means randomized block design randomly assigned rank experimental design regression model rejected restrictions scores SSAB SSBL SSRES SSTO subjects sum of squares Summary Table Entry test statistic treatment combinations treatment levels trend type I error vector within-blocks Y₁ Y₂ Yijk Yijklz αι μι ΣΣ ΣΣΣ στ ΣΥ аз пр