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 — reference:ft_statfun_pooledt [2018/08/23 14:43] (current) Line 1: Line 1: + =====  FT_STATFUN_POOLEDT ===== + + Note that this reference documentation is identical to the help that is displayed in MATLAB when you type "help ft_statfun_pooledT"​. + + <​html><​pre>​ + <​font color=green>​FT_STATFUN_POOLEDT​ computes the pooled t-value over a number of replications. The + idea is that you compute a contrast between two conditions per subject The t-values + are pooled over subjects and compared against the pooled pseudo-values. Since + according to H0 the expected t-value for each subject value is zero, the difference + between the pooled t-value and the pseudo-value (which is set to zero) is a + fixed-effects statistic. + ​ + The computation of the difference between pooled t-values can be repeated after + randomly permuting the t-values and pseudo-values within the subjects. Each random + permutation gives you an estimate of the difference. The random permutations build + up a randomization distributin,​ against which you can compare the observed pooled + t-values. + ​ + The statistical inference based on the comparison of the observed pooled t-values + with the randomization distribution is not a fixed-effect statistic, one or a few + outlier will cause the randomization distribution to broaden and result in the + conclusion of "not significant"​. + ​ + Use this function by calling one of the high-level statistics functions as + [stat] = ft_timelockstatistics(cfg,​ timelock1, timelock2, ...) + [stat] = ft_freqstatistics(cfg,​ freq1, freq2, ...) + [stat] = ft_sourcestatistics(cfg,​ source1, source2, ...) + with the following configuration option + cfg.statistic = '​ft_statfun_pooledT'​ + + Configuration options that are relevant for this function are + cfg.ivar ​     = number, index into the design matrix with the independent variable + + See also <​font color=green>​FT_TIMELOCKSTATISTICS,​ <​font color=green>​FT_FREQSTATISTICS​ or <​font color=green>​FT_SOURCESTATISTICS​ +