Abstract
While the applied psychology community relies on statistics to assist drawing conclusions from quantitative data, the methods being used mostly today do not reflect several of the advances in statistics that have been realized over the past decades. We show in this paper how a number of issues with how statistical analyses are presently executed and reported in the literature can be addressed by applying more modern methods. Unfortunately, such new methods are not always supported by widely available statistical packages, such as SPSS, which is why we also introduce a new software platform, called ILLMO (for Interactive Log-Likelihood MOdeling), which offers an intuitive interface to such modern statistical methods. In order to limit the complexity of the material being covered in this paper, we focus the discussion on a fairly simple, but nevertheless very frequent and important statistical task, i.e., comparing two experimental conditions.
| Original language | English |
|---|---|
| Pages (from-to) | 1240-1261 |
| Number of pages | 22 |
| Journal | Behavior Research Methods |
| Volume | 53 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - Jun 2021 |
Keywords
- Confidence intervals
- Effect size
- Empirical likelihood
- Exploratory statistics
- Hypothesis testing
- Interactive statistics
- Likert scales
- t test
- Wilks’ theorem
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