# Evaluate difference between a group mean curve and a constant model using the comparison of model fit (F-test) Execute a t-test based on the comparison of improvement of model fit from a single group mean curve to the fit of both a group mean curve and a constant linear model. This statistic identifies within-class differential evolution, and test whether the population average time curve is flat or not. **n** constant linear model are generated to match the **n** individual trajetories. The **Null** distribution is generated by permuting the **n** group individuals and the **n** constant trajectories. The real improvement in model fit for the real group membership versus flat trajectories is then compared to the **Null** distribution of model fit improvement, similarly to `santaR_pvalue_fit`. Adapted from Storey and al. 'Significance analysis of time course microarrayexperiments', PNAS, 2005 [1] . ```r santaR_pvalue_fit_within(SANTAGroup, nPerm = 1000) ``` ## Arguments - `SANTAGroup`: A fitted group extracted from a **SANTAObj** generated by `santaR_fit`. - `nPerm`: (int) Number of permutations. Default 1000. ## Returns A **p-value** ## Examples ```r ## 56 measurements, 8 subjects, 7 unique time-points ## Default parameter values decreased to ensure an execution < 2 seconds Yi <- acuteInflammation$data$var_3 ind <- acuteInflammation$meta$ind time <- acuteInflammation$meta$time group <- acuteInflammation$meta$group grouping <- get_grouping(ind, group) inputMatrix <- get_ind_time_matrix(Yi, ind, time) SANTAObj <- santaR_fit(inputMatrix, df=5, grouping=grouping, verbose=TRUE) SANTAGroup <- SANTAObj$groups[[1]] #SANTAGroup <- SANTAObj$groups$Group1 santaR_pvalue_fit_within(SANTAGroup, nPerm=500) # ~0.6726747 ``` ## References [1] Storey, J. D., Xiao, W., Leek, J. T., Tompkins, R. G. & Davis, R. W. Significance analysis of time course microarray experiments. **Proceedings of the National Academy of Sciences of the United States of America** 102 , 12837-42 (2005). ## See Also Inter-group comparison with `santaR_pvalue_fit`

santaR_pvalue_fit_within function