Statistical Analysis of Efficient Unbalanced Factorial Designs for Two-Color Microarray Experiments

Table 2

Classical ANOVA of log intensities for duplicated A-loop design component of Figure 2 on ID_REF #30 from Zou et al. (2005) using output from SAS PROC MIXED (code in Figure 3).

Type 3 analysis of variance
Source	DF^†	Sum of squares	Mean square	Expected mean square	Error term	Error DF	value	Pr > F^†
Trt	2	0.7123	0.3561	Var(Residual) + 1.5 Var(sample(inoc^*time)) + Q(inoc,inoc^*time)	MS(sample(inoc^*time))	6	3.13	0.1172
Time	2	3.7737	1.8868	Var(Residual) + 2 Var(sample(inoc^*time)) + 2Var(array(time)) + Q(time,inoc^*time)	1.3333 MS(array(time)) + 1.3333 MS(sample(inoc^*time)) 1.6667 MS(Residual)	13.969	3.27	0.0683
Inoc^*time	4	0.6294	0.1573	Var(Residual) + 1.5 Var(sample(inoc^*time)) + Q(inoc^*time)	MS(sample(inoc^*time))	6	1.38	0.3435
Dye	1	0.0744	0.0744	Var(Residual) + Q(dye)	MS(Residual)	5	2.19	0.1989
Rep(inoc^*time)	6	0.6826	0.1137	Var(Residual) + 1.5 Var(sample(inoc^*time))	MS(Residual)	5	3.35	0.1030
Array(time)	12	4.3330	0.3610	Var(Residual) + 1.5 Var(array(time))	MS(Residual)	5	10.63	0.0085
Residual	5	0.1699	0.0339	Var(Residual)	.	.	.	.

^†Degrees of freedom.
^‡P-value.