Table 1.
Data set | Most parsimonious log-linear model | Likelihood ratio χ2 | p |
---|---|---|---|
A, Duration | Cell type × duration × label = label + duration | G2(5) = 1.226 | 0.94 |
B, L-EGF only | Cell type × treatment × label = treatment × label | G2(6) = 0.6218 | 0.99 |
C, PD153035 plus L-EGF | Cell type × treatment × label = treatment × label | G2(6) = 9.985 | 0.24 |
D, PD153035 only | Cell type × treatment × label = treatment × label | G2(6) = 2.260 | 0.81 |
E, K252a only | Cell type × treatment × label = treatment × label + cell type × label | G2(3) = 0.5128 | 0.92 |
Shown are the most parsimonious log-linear models with their associated likelihood ratio χ2 (degrees of freedom in subscript) and p value. [Contrary to most other statistical techniques, high values of the test statistic combined with a significant p value indicate that the evaluated model does not adequately explain the sample frequencies. Thus, a model adequately describing the data distribution is associated with a low value ofG2 combined with a nonsignificant pvalue; i.e., p > 0.05 (Rodgers, 1998).]