Getting rid of the Chi-square and Log-likelihood tests for analysing vocabulary differences between corpora

On the multi _ chi-square tests and their data complexity

Chi-square tests are generally used for distinguishing purposes; however when they are combined to simultaneously test several independent variables, extra notation is required. In this study, the chi-square statistics in some previous works is revealed to be computed half of its real value. Therefore, the notion of Multi _ Chi-square tests is formulated to avoid possible future confusions. In ...

Inadequacy of the chi-squared test to examine vocabulary differences between corpora

Pearson's chi-squared test is probably the most popular statistical test used in corpus linguistics, particularly for studying linguistic variations between corpora. Oakes and Farrow (Literary and Linguistic Computing, 2007, 22, 85-99) proposed various adaptations of this test in order to allow for the simultaneous comparison of more than two corpora, while also yielding an almost correct Type ...

Text S1. Relationship between one-sided chi-square test and Bayesian log-likelihood score (LLS) method

Here we show that the one-sided chi-square test used for evaluating the significance of the overlap between the RH network and other existing datasets and the Bayesian loglikelihood score (LLS) approach used for integrating diverse datasets [1,2] are closely related. The Fisher’s exact test was used instead of the chi-square test when the expected value in a cell of the contingency table was ≤ ...

Chi-Square Tests for Comparison Weighted Histograms

Weighted histograms in Monte-Carlo simulations are often used for the estimation of probability density functions. They are obtained as a result of random experiment with random events that have weights. In this paper the bin contents of a weighted histogram are considered as a sum of random variables with a random number of terms. Generalizations of the classical chi-square test for comparing ...

Chi-square Tests for Parameter Stability