janhove.github.io 7. 3. 2023Adjusting to Julia: Piecewise regression – janhove.github.io 23. 2. 2023Adjusting to Julia: Tea tasting – janhove.github.io 9. 2. 2023Adjusting to Julia: The Levenshtein algorithm – janhove.github.io 20. 12. 2022Adjusting to Julia: Generating the Fibonacci sequence – janhove.github.io 18. 2. 2022In research, don't do things you don't see the point of – janhove.github.io 17. 2. 2022An R function for computing Levenshtein distances between texts using the word as the unit of comparison – janhove.github.io 29. 6. 2021The consequences of controlling for a post-treatment variable – janhove.github.io 16. 12. 2020Quantitative methodology: An introduction – janhove.github.io 2. 9. 2020Capitalising on covariates in cluster-randomised experiments – janhove.github.io 29. 6. 2020Tutorial: Visualising statistical uncertainty using model-based graphs – janhove.github.io 12. 6. 2020Interpreting regression models: a reading list – janhove.github.io 23. 5. 2020Nonparametric tests aren't a silver bullet when parametric assumptions are violated – janhove.github.io 5. 5. 2020Tutorial: Obtaining directly interpretable regression coefficients by recoding categorical predictors – janhove.github.io 18. 2. 2020Baby steps in Bayes: Incorporating reliability estimates in regression models – janhove.github.io 21. 1. 2020Baby steps in Bayes: Accounting for measurement error on a control variable – janhove.github.io 5. 12. 2019Five suggestions for simplifying research reports – janhove.github.io 28. 11. 2019Drawing scatterplot matrices – janhove.github.io 28. 10. 2019Adjusting for a covariate in cluster-randomised experiments – janhove.github.io 11. 9. 2019Collinearity isn't a disease that needs curing – janhove.github.io 7. 8. 2019Interactions in logistic regression models – janhove.github.io 16. 4. 2019Walkthrough: A significance test for a two-group comparison – janhove.github.io 11. 4. 2019Before worrying about model assumptions, think about model relevance – janhove.github.io 14. 1. 2019Guarantees in the long run vs. interpreting the data at hand: Two analyses of clustered data – janhove.github.io 20. 12. 2018Baby steps in Bayes: Recoding predictors and homing in on specific comparisons – janhove.github.io 29. 10. 2018A closer look at a classic study (Bailey et al. 1974) – janhove.github.io 26. 9. 2018Introducing cannonball - Tools for teaching statistics – janhove.github.io 12. 9. 2018Looking for comments on a paper on model assumptions – janhove.github.io 27. 7. 2018Baby steps in Bayes: Piecewise regression with two breakpoints – janhove.github.io 6. 7. 2018A data entry form with sanity checks – janhove.github.io 4. 7. 2018Baby steps in Bayes: Piecewise regression – janhove.github.io 27. 6. 2018A brief comment on research questions – janhove.github.io 25. 4. 2018Checking model assumptions without getting paranoid – janhove.github.io 12. 2. 2018Consider generalisability – janhove.github.io 20. 11. 2017Suggestions for more informative replication studies – janhove.github.io 24. 10. 2017Increasing power and precision using covariates – janhove.github.io 19. 9. 2017Confidence interval-based optional stopping – janhove.github.io 14. 9. 2017Creating comparable sets of stimuli – janhove.github.io 24. 8. 2017Draft: Replication success as predictive utility – janhove.github.io 14. 7. 2017Abandoning standardised effect sizes and opening up other roads to power – janhove.github.io 26. 6. 2017Interactions between continuous variables – janhove.github.io 12. 5. 2017Tutorial: Adding confidence bands to effect displays – janhove.github.io 23. 4. 2017Tutorial: Plotting regression models – janhove.github.io 22. 2. 2017Confidence intervals for standardised mean differences – janhove.github.io 15. 2. 2017Which predictor is most important? Predictive utility vs. construct importance – janhove.github.io 31. 1. 2017Automatise repetitive tasks – janhove.github.io 20. 12. 2016Some illustrations of bootstrapping – janhove.github.io 21. 11. 2016What data patterns can lie behind a correlation coefficient? – janhove.github.io 16. 11. 2016Common-language effect sizes – janhove.github.io 31. 10. 2016The Centre for Open Science's Preregistration Challenge: Why it's relevant and some recommended background reading – janhove.github.io 30. 8. 2016Tutorial: Drawing a dot plot – janhove.github.io 18. 8. 2016R tip: Ordering factor levels more easily – janhove.github.io 5. 7. 2016Classifying second-language learners as native- or non-nativelike: Don't neglect classification error rates – janhove.github.io 21. 6. 2016Tutorial: Drawing a boxplot – janhove.github.io 13. 6. 2016Tutorial: Drawing a line chart – janhove.github.io 2. 6. 2016Tutorial: Drawing a scatterplot – janhove.github.io 18. 5. 2016Surviving the ANOVA onslaught – janhove.github.io 22. 4. 2016Why reported R² values are often too high – janhove.github.io 1. 4. 2016On correcting for multiple comparisons: Five scenarios – janhove.github.io 23. 2. 2016Silly significance tests: The main effects no one is interested in – janhove.github.io 16. 2. 2016Experiments with intact groups: spurious significance with improperly weighted t-tests – janhove.github.io 14. 12. 2015Some advantages of sharing your data and code – janhove.github.io 17. 11. 2015Drawing a scatterplot with a non-linear trend line – janhove.github.io 2. 11. 2015Causes and consequences of unequal sample sizes – janhove.github.io 16. 10. 2015The problem with cutting up continuous variables and what to do when things aren't linear – janhove.github.io 17. 9. 2015Analysing experiments with intact groups: the problem and an easy solution – janhove.github.io 2. 9. 2015Covariate adjustment in logistic mixed models: Is it worth the effort? – janhove.github.io 24. 8. 2015Controlling for confounding variables in correlational research: Four caveats – janhove.github.io 17. 7. 2015Covariate adjustment in logistic regression — and some counterintuitive findings – janhove.github.io 18. 6. 2015Some tips on preparing your data for analysis – janhove.github.io 8. 6. 2015Silly significance tests: Tests unrelated to the genuine research questions – janhove.github.io 14. 4. 2015Power simulations for comparing independent correlations – janhove.github.io 16. 3. 2015More on why I don't like standardised effect sizes – janhove.github.io 3. 3. 2015A more selective approach to reporting statistics – janhove.github.io 26. 2. 2015Explaining key concepts using permutation tests – janhove.github.io 21. 2. 2015Thinking about graphs – janhove.github.io 5. 2. 2015Why I don't like standardised effect sizes – janhove.github.io 14. 1. 2015Overaccuracy and false precision – janhove.github.io 7. 1. 2015Some alternatives to bar plots – janhove.github.io 18. 11. 2014The curious neglect of covariates in discussions of statistical power – janhove.github.io 28. 10. 2014Assessing differences of significance – janhove.github.io 15. 10. 2014Silly significance tests: Tautological tests – janhove.github.io 26. 9. 2014Silly significance tests: Balance tests – janhove.github.io 12. 9. 2014A purely graphical explanation of p-values – janhove.github.io 20. 8. 2014Calibrating p-values in 'flexible' piecewise regression models – janhove.github.io 14. 8. 2014Analysing pretest/posttest data – janhove.github.io
7. 3. 2023Adjusting to Julia: Piecewise regression – janhove.github.io 23. 2. 2023Adjusting to Julia: Tea tasting – janhove.github.io 9. 2. 2023Adjusting to Julia: The Levenshtein algorithm – janhove.github.io 20. 12. 2022Adjusting to Julia: Generating the Fibonacci sequence – janhove.github.io 18. 2. 2022In research, don't do things you don't see the point of – janhove.github.io 17. 2. 2022An R function for computing Levenshtein distances between texts using the word as the unit of comparison – janhove.github.io 29. 6. 2021The consequences of controlling for a post-treatment variable – janhove.github.io 16. 12. 2020Quantitative methodology: An introduction – janhove.github.io 2. 9. 2020Capitalising on covariates in cluster-randomised experiments – janhove.github.io 29. 6. 2020Tutorial: Visualising statistical uncertainty using model-based graphs – janhove.github.io 12. 6. 2020Interpreting regression models: a reading list – janhove.github.io 23. 5. 2020Nonparametric tests aren't a silver bullet when parametric assumptions are violated – janhove.github.io 5. 5. 2020Tutorial: Obtaining directly interpretable regression coefficients by recoding categorical predictors – janhove.github.io 18. 2. 2020Baby steps in Bayes: Incorporating reliability estimates in regression models – janhove.github.io 21. 1. 2020Baby steps in Bayes: Accounting for measurement error on a control variable – janhove.github.io 5. 12. 2019Five suggestions for simplifying research reports – janhove.github.io 28. 11. 2019Drawing scatterplot matrices – janhove.github.io 28. 10. 2019Adjusting for a covariate in cluster-randomised experiments – janhove.github.io 11. 9. 2019Collinearity isn't a disease that needs curing – janhove.github.io 7. 8. 2019Interactions in logistic regression models – janhove.github.io 16. 4. 2019Walkthrough: A significance test for a two-group comparison – janhove.github.io 11. 4. 2019Before worrying about model assumptions, think about model relevance – janhove.github.io 14. 1. 2019Guarantees in the long run vs. interpreting the data at hand: Two analyses of clustered data – janhove.github.io 20. 12. 2018Baby steps in Bayes: Recoding predictors and homing in on specific comparisons – janhove.github.io 29. 10. 2018A closer look at a classic study (Bailey et al. 1974) – janhove.github.io 26. 9. 2018Introducing cannonball - Tools for teaching statistics – janhove.github.io 12. 9. 2018Looking for comments on a paper on model assumptions – janhove.github.io 27. 7. 2018Baby steps in Bayes: Piecewise regression with two breakpoints – janhove.github.io 6. 7. 2018A data entry form with sanity checks – janhove.github.io 4. 7. 2018Baby steps in Bayes: Piecewise regression – janhove.github.io 27. 6. 2018A brief comment on research questions – janhove.github.io 25. 4. 2018Checking model assumptions without getting paranoid – janhove.github.io 12. 2. 2018Consider generalisability – janhove.github.io 20. 11. 2017Suggestions for more informative replication studies – janhove.github.io 24. 10. 2017Increasing power and precision using covariates – janhove.github.io 19. 9. 2017Confidence interval-based optional stopping – janhove.github.io 14. 9. 2017Creating comparable sets of stimuli – janhove.github.io 24. 8. 2017Draft: Replication success as predictive utility – janhove.github.io 14. 7. 2017Abandoning standardised effect sizes and opening up other roads to power – janhove.github.io 26. 6. 2017Interactions between continuous variables – janhove.github.io 12. 5. 2017Tutorial: Adding confidence bands to effect displays – janhove.github.io 23. 4. 2017Tutorial: Plotting regression models – janhove.github.io 22. 2. 2017Confidence intervals for standardised mean differences – janhove.github.io 15. 2. 2017Which predictor is most important? Predictive utility vs. construct importance – janhove.github.io 31. 1. 2017Automatise repetitive tasks – janhove.github.io 20. 12. 2016Some illustrations of bootstrapping – janhove.github.io 21. 11. 2016What data patterns can lie behind a correlation coefficient? – janhove.github.io 16. 11. 2016Common-language effect sizes – janhove.github.io 31. 10. 2016The Centre for Open Science's Preregistration Challenge: Why it's relevant and some recommended background reading – janhove.github.io 30. 8. 2016Tutorial: Drawing a dot plot – janhove.github.io 18. 8. 2016R tip: Ordering factor levels more easily – janhove.github.io 5. 7. 2016Classifying second-language learners as native- or non-nativelike: Don't neglect classification error rates – janhove.github.io 21. 6. 2016Tutorial: Drawing a boxplot – janhove.github.io 13. 6. 2016Tutorial: Drawing a line chart – janhove.github.io 2. 6. 2016Tutorial: Drawing a scatterplot – janhove.github.io 18. 5. 2016Surviving the ANOVA onslaught – janhove.github.io 22. 4. 2016Why reported R² values are often too high – janhove.github.io 1. 4. 2016On correcting for multiple comparisons: Five scenarios – janhove.github.io 23. 2. 2016Silly significance tests: The main effects no one is interested in – janhove.github.io 16. 2. 2016Experiments with intact groups: spurious significance with improperly weighted t-tests – janhove.github.io 14. 12. 2015Some advantages of sharing your data and code – janhove.github.io 17. 11. 2015Drawing a scatterplot with a non-linear trend line – janhove.github.io 2. 11. 2015Causes and consequences of unequal sample sizes – janhove.github.io 16. 10. 2015The problem with cutting up continuous variables and what to do when things aren't linear – janhove.github.io 17. 9. 2015Analysing experiments with intact groups: the problem and an easy solution – janhove.github.io 2. 9. 2015Covariate adjustment in logistic mixed models: Is it worth the effort? – janhove.github.io 24. 8. 2015Controlling for confounding variables in correlational research: Four caveats – janhove.github.io 17. 7. 2015Covariate adjustment in logistic regression — and some counterintuitive findings – janhove.github.io 18. 6. 2015Some tips on preparing your data for analysis – janhove.github.io 8. 6. 2015Silly significance tests: Tests unrelated to the genuine research questions – janhove.github.io 14. 4. 2015Power simulations for comparing independent correlations – janhove.github.io 16. 3. 2015More on why I don't like standardised effect sizes – janhove.github.io 3. 3. 2015A more selective approach to reporting statistics – janhove.github.io 26. 2. 2015Explaining key concepts using permutation tests – janhove.github.io 21. 2. 2015Thinking about graphs – janhove.github.io 5. 2. 2015Why I don't like standardised effect sizes – janhove.github.io 14. 1. 2015Overaccuracy and false precision – janhove.github.io 7. 1. 2015Some alternatives to bar plots – janhove.github.io 18. 11. 2014The curious neglect of covariates in discussions of statistical power – janhove.github.io 28. 10. 2014Assessing differences of significance – janhove.github.io 15. 10. 2014Silly significance tests: Tautological tests – janhove.github.io 26. 9. 2014Silly significance tests: Balance tests – janhove.github.io 12. 9. 2014A purely graphical explanation of p-values – janhove.github.io 20. 8. 2014Calibrating p-values in 'flexible' piecewise regression models – janhove.github.io 14. 8. 2014Analysing pretest/posttest data – janhove.github.io