- Jan 25, 2025
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Gael MILLOT authored
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- Dec 09, 2024
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Gael MILLOT authored
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- Dec 05, 2024
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Gael MILLOT authored
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- Dec 04, 2024
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Gael MILLOT authored
release v12.5: error fixed so that now quali columns of required.var are factors when FAKE_VAR column is added
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- Aug 05, 2024
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Gael MILLOT authored
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- Jul 24, 2024
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Gael MILLOT authored
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- Jul 12, 2024
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Gael MILLOT authored
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- May 06, 2024
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Gael MILLOT authored
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- May 03, 2024
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Gael MILLOT authored
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Gael MILLOT authored
release v12.2: Warning message added in title of pre analyse of the response var when log2 transfo: NEG VALUES ARE REMOVED. Nesting detection added
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- May 02, 2024
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Gael MILLOT authored
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Gael MILLOT authored
Warning message added in title of pre analyse of the response var when log2 transfo: NEG VALUES ARE REMOVED
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Gael MILLOT authored
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Gael MILLOT authored
release v12.0: New ref.class parameter to set the reference class of the contrast.kind = "contr.treatment" estimate computations
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Gael MILLOT authored
release v11.4: lme4::lmer replaced by lmerTest::lmer to get the p values of the fixed effects in mixed models
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- Apr 05, 2024
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Gael MILLOT authored
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Gael MILLOT authored
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Gael MILLOT authored
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Gael MILLOT authored
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- Apr 04, 2024
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Gael MILLOT authored
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Gael MILLOT authored
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- Jan 12, 2024
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Gael MILLOT authored
release v9.0: bug fixed in the checking of model1 writting, limma_v1.0.R added, anova_contrasts.config file updated
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- Jun 27, 2023
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Gael MILLOT authored
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- Jun 26, 2023
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Gael MILLOT authored
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Gael MILLOT authored
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Gael MILLOT authored
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Gael MILLOT authored
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Gael MILLOT authored
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Gael MILLOT authored
release v7.11: Graphical analysis of the response variable, independently of the predictive variables
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- May 30, 2023
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Gael MILLOT authored
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- Aug 19, 2022
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Gael MILLOT authored
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- Aug 18, 2022
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Gael MILLOT authored
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Gael MILLOT authored
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Gael MILLOT authored
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- Aug 17, 2022
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Gael MILLOT authored
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- May 03, 2022
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Gael MILLOT authored
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- May 02, 2022
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Gael MILLOT authored
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- Feb 14, 2022
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Gael MILLOT authored
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- Jan 27, 2022
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Gael MILLOT authored
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- Jan 26, 2022
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Gael MILLOT authored
release v7.1.0: the other way to compute the p values for mixed model and large dataset is now correctly displayed
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