Study Preregistration: [Study title]

Preregistration template for a confirmatory study: hypotheses, design, sampling, variables and analysis plan, written and time-stamped before data are collected or examined. The topics follow the concepts used in common open-science preregistration forms (such as those offered on the Open Science Framework), written in original words for this collection. Replace every [bracketed] value and every line marked Example.

1. Study information

This section states what the study asks and what the authors predict.

1.1 Research questions

[State the research question or questions in one or two sentences each.]

1.2 Hypotheses

1.3 Existing data

Select one and explain:

• Registration prior to creation of data
• Registration prior to any human observation of the data
• Registration prior to accessing the data
• Registration prior to analysis of the data
• Registration following analysis of the data

Explanation: [What data exist, who has seen them and what, and why this does not bias the confirmatory tests.]

2. Design plan

The design plan defines the study type, conditions and assignment.

3. Sampling plan

This section explains who will be sampled, how many and when collection stops.

3.1 Data collection procedures

[Population, recruitment source, inclusion and exclusion criteria, payment, and the timeline of data collection.]

3.2 Sample size

[Target number of participants or observations after exclusions.]

3.3 Sample size rationale

Example: To detect $d = 0.40$ with 90% power at one-sided $\alpha = 0.025$ in a two-group comparison, the required sample is:

We will recruit 145 per group to allow for about 9% exclusions.

3.4 Stopping rule

[State when data collection ends. Example: Data collection stops when 290 complete responses meeting inclusion criteria are recorded or on YYYY-MM-DD, whichever comes first. No interim analyses will be run.]

4. Variables

The variables section defines what is manipulated, measured and computed.

Indices: [How composite measures are computed, for example the mean of items 1-8 after reverse-scoring items 3 and 6.]

5. Analysis plan

This section describes the confirmatory analyses and how results will be judged.

5.1 Statistical models

5.2 Transformations

[Planned transformations, centring or recoding, and the coding of categorical predictors.]

5.3 Inference criteria

[Decision rule, for example one-sided $p < 0.025$ for H1; Holm correction across H2 and H3; equivalence test with bounds of $d = \pm 0.20$ to interpret null results; Bayes factor thresholds if used.]

5.4 Data exclusion

[Rules for excluding participants or observations, decided now. Example: Exclude participants who fail either attention check, complete the study in under 5 minutes, or report having taken the test before. Exclude reaction times more than 3 SD from the participant mean.]

5.5 Missing data

[How missing data will be handled, for example listwise deletion if under 5% missing, otherwise multiple imputation with 20 imputations using all study variables.]

5.6 Exploratory analyses

[Analyses you may run that are not confirmatory. List them so readers can see they were anticipated, and state that they will be reported as exploratory.]

6. Other

Additional information and links:

7. Timestamps and deviations

This log records when the plan was frozen and every later change.

Standard and licence note

Based on common open-science practice for study preregistration, with topics similar to widely used preregistration forms such as those on the Open Science Framework (https://osf.io/registries). This template is original text written for this collection and reproduces no form text. Template licence: MIT.