Nested Designs - Scholar

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Tests wrt Random Effects Source SS MS Num DF Num F Ratio Prob > F Hybrid 2275.96 568.99 4 69.9579
Least Squares Means Table Level Least Sq Mean Std Error Mean 1 45.524375 0.58214105 45.5244 2 48.150857 0.58214105 48.1509 3 51.296105 0.58214105 51.2961 4 54.449997 0.58214105 54.4500 5 57.759636 0.58214105 57.7596 LSMeans Differences Tukey HSD α=0.050 Q=3.29108 Level Least Sq Mean 5 A 57.759636 4 B 54.449997 3 C 51.296105 2 D 48.150857 1 D 45.524375 Levels not connected by same letter are significantly different. This output becomes Table 2 in the results section of the conclusion. SAS Implementation The SAS model statement in PROC ANOVA or PROC GLM would be MODEL TRANSPIR = HYBRID POT(HYBRID) PLANT(POT HYBRID); F-Tests in SAS The SAS Statements: PROC ANOVA; CLASS HYBRID POT PLANT; MODEL TRANSPIR = HYBRID POT(HYBRID) PLANT(POT HYBRID); will perform only the third of the three desired F-tests automatically. The first two hypotheses, whose F-tests do not have MSE in the denominator, will not be performed automatically. This is because SAS automatically uses the mean squared error (MSE) as the denominator for all F- tests, so that the F values that SAS produces for the first and second tests are incorrect. There are two ways to get the correct values. nested01.docx 17 4/5/2012
Page 1 and 2: Nested Designs Nested designs, also
Page 3 and 4: Quantitative Response = Constant (g
Page 5 and 6: Random effects are random variables
Page 7 and 8: o (dispersion) Yijkl iBjiCki, j
Page 9 and 10: Symbolically, H0: σplants = 0, ver
Page 11 and 12: 4. Design Significance level 0.05
Page 13 and 14: Alternative Allocation of Experimen
Page 15: Estimating Variance Components in J
Page 19 and 20: For random effects, the hypotheses
Page 21 and 22: Methods The effects on mean human f
Page 23 and 24: ANOVA Table ANOVA -----------------
Page 25: ii) Write a "results" paragraph. Do

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