What’s the best preregistration template set for common study designs?

If you mean a practical “template library” that covers most common designs, I’d use OSF as the home base, then switch templates when the design has special preregistration needs. OSF currently offers dedicated forms for several of these designs.

If you only want a small set

I'd keep these five in a lab's standard toolkit:

1. OSF Preregistration — default for most quantitative studies.
2. AsPredicted — lightweight option for straightforward experiments.
3. PRP-QUANT — quantitative psychology when you want more specificity.
4. OSF Qualitative Preregistration — qualitative/mixed-methods work.
5. OSF Generalized Systematic Review Registration — reviews/meta-analyses.

OSF is particularly convenient because the registrations are formally time-stamped/locked and can be made public or embargoed; the important methodological point is to clearly distinguish what was specified prospectively from what was decided later.

One caveat: “best” depends heavily on what you want the preregistration to accomplish. A short AsPredicted registration can be perfectly appropriate for a simple experiment, whereas using it for a complicated longitudinal or secondary-data analysis can leave important researcher degrees of freedom unspecified.

If you tell me your field (e.g. psychology, neuroscience, economics, education, biology) and 3–5 designs you commonly run, I can turn this into a one-page lab preregistration template set, including exactly which sections to require for each design.

The "best" preregistration template depends heavily on your specific study design, methodology, and how granular you need your plan to be. The Center for Open Science hosts standard templates on the OSF Registries , alongside streamlined alternatives like AsPredicted.

The top-recommended preregistration template sets categorized by common study designs include the following:

• AsPredicted Template
  • Best for: Simple, straightforward experimental or survey designs and researchers new to preregistration.
  • Why use it: It features a concise, standardized 8-question format covering hypotheses, data collection stopping rules, outliers/exclusions, and primary analyses. Most journals instantly recognize and accept this format.
• OSF Standard Preregistration (“Preregistration Challenge” Template)
  • Best for: Standard confirmatory laboratory experiments, randomized controlled trials (RCTs), and psychology/behavioral studies.
  • Why use it: It is comprehensive, walking you through rigorous, step-by-step documentation of variables, experimental design, exact blinding procedures, and specific statistical models.
• Secondary Data Pre-Registration Template
  • Best for: Studies analyzing existing datasets where data collection has already occurred, but you haven't yet looked at the specific variables or run tests for your research question.
  • Why use it: It explicitly adapts questions to address access constraints, data subsets, and pre-existing knowledge of the data, ensuring clear separation from exploratory data mining.
• Qualitative Preregistration Template (Haven & van Grootel)
  • Best for: Primarily qualitative or mixed-methods research (e.g., interviews, thematic analysis, ethnography).
  • Why use it: Traditional templates focus heavily on p-values and sample size power calculations. This specialized template adapts the preregistration framework to outline sampling strategies for text/interviews, coding frameworks, and qualitative inference criteria.
• Replication Recipe (Brandt et al.)
  • Best for: Direct or conceptual replications of published studies.
  • Why use it: It ensures you document precisely what is being copied from the original study, what deviations (if any) are intentional, and how success or failure of the replication will be statistically evaluated.

If you want to narrow this down, tell me:

• What is your study design (e.g., experimental, correlational, qualitative, secondary data)?
• Are you planning to register on a specific platform like OSF or AsPredicted?

I can recommend the exact template that fits your project.

The "best" preregistration template depends heavily on your study design and how much granular detail you need to lock down . Platforms like the Center for Open Science Blog and OSF Support host standardized templates tailored to different methodologies.

The top template sets categorized by common study designs include:

• Standard / General Quantitative (Experiments & Surveys):
  • OSF Preregistration (Standard): The most comprehensive general-purpose template. Best for standard lab experiments, randomized controlled trials (RCTs), and psychology/behavioral studies. It forces you to thoroughly detail hypotheses, variables, blinding, sample size justifications, and analysis plans.
  • AsPredicted: A streamlined, 8-question format. Perfect if you want a fast, punchy, highly readable preregistration without the exhaustive sub-questions of the full OSF standard form.
• Secondary / Existing Data Analysis:
  • Secondary Data Preregistration: Specifically designed when you are analyzing a dataset you haven't collected yet or have not yet looked at/analyzed for this specific research question. It prompts you to clarify your access level, whether data are already public or restricted, and how you will ensure you are blind to key outcomes.
• Systematic Reviews & Meta-Analyses:
  • Generalized Systematic Review Template: Tailored for literature synthesis. It covers search strings, inclusion/exclusion criteria, screening procedures, and data extraction/synthesis plans. (Often mirrors PRISMA-P guidelines).
• Qualitative and Mixed Methods Research:
  • Preregistration for Qualitative Research: Designed for inductive or qualitative designs (e.g., interviews, ethnography). It adapts traditional preregistration logic—which usually assumes rigid hypothesis-testing—to fit iterative data collection, reflexive thematic analysis, and flexible sampling strategies.
• Specialized / Complex Designs:
  • fMRI & Neuroimaging Template: Highly specific for neuroimaging workflows, addressing spatial normalization, smoothing, multiple-comparison corrections, and ROI definitions.
  • Mathematical and Computational Models: Built for registering model parameters, simulation architectures, and optimization routines before fitting them to empirical data.

Researcher Perspectives

Researchers often weigh the friction of detailed forms against the speed of quick ones:

I like AsPredicted because it’s short enough that co-authors actually read and agree on every line, whereas the massive OSF form sometimes feels like writing a mini grant application before you even start.

For complex experimental designs with multiple secondary endpoints, the standard OSF preregistration is a lifesaver because it doesn't let you gloss over ambiguous analysis decisions.

If you'd like to narrow this down, tell me:

• What is your specific study design (e.g., RCT, secondary data analysis, qualitative interview study)?
• Are you planning to register on OSF, AsPredicted , or another platform?

I can recommend the exact template and outline the key sections you'll need to fill out.

If you want a small, practical template set that covers most research designs, I’d use OSF as the default registry and switch templates based on the design. OSF itself lists the standard OSF Preregistration as its most commonly used general-purpose form, alongside several design-specific templates.

OSF currently provides all of these specialized options.

If I were setting up a lab-wide standard

I'd make the decision rule:

1. Default → OSF Preregistration
2. Psychology → PRP-QUANT when the additional detail is worthwhile
3. Existing dataset → Secondary Data Preregistration
4. Replication → Replication Recipe
5. Qualitative → Qualitative Preregistration
6. Review → Generalized Systematic Review
7. Simulation → Simulation Studies
8. Very simple study → AsPredicted

The key distinction is template vs. registry: these are largely different ways of specifying your plan; OSF is the repository/registration infrastructure. An ordinary preregistration gives you a timestamped record, whereas a Registered Report adds peer review of the study plan before the results are known.

For most quantitative studies, I'd personally choose OSF Preregistration over AsPredicted unless brevity is the priority. The more comprehensive template forces you to specify things like sampling/stopping rules, variables, exclusions, statistical models, missing data, and confirmatory vs. exploratory analyses—exactly the decisions where analytical flexibility can otherwise creep in.

If you tell me your field + 2–3 study designs you commonly run, I can also give you a minimal “house preregistration template” that combines the best parts of these into one decision-tree/checklist.

If you mean “what template should I actually use for different kinds of studies?”, I’d use OSF as the default ecosystem, then switch to a specialized template when the design warrants it. OSF currently offers general and design-specific templates, including secondary-data, qualitative, EEG/ERP, eye-tracking, systematic-review, simulation, and replication templates.

My recommended template set

If you only want one template

Use OSF Preregistration.

It's the safest general-purpose choice: OSF describes it as its standard, comprehensive template, and it remains the most broadly applicable option.

If you're doing psychology

I'd actually consider PRP-QUANT the better default for a conventional quantitative psychology paper. It's specifically intended for quantitative psychological studies, and the APA describes its newer preregistration standards as deliberately thorough and designed to encourage detailed upfront planning.

The important distinction

Don't choose based solely on the statistical test. For example, an ANOVA vs. regression isn't usually enough reason to use different templates. Choose based on what creates distinctive researcher degrees of freedom:

• Primary data + conventional experiment → OSF/PRP-QUANT
• Existing data → Secondary Data template
• Replication → Replication Recipe
• Qualitative → Qualitative template
• Systematic review/meta-analysis → Systematic Review template
• Simulation → ADEMP
• Specialized measurement modality → modality-specific template
• Peer-reviewed preregistration → Registered Report

One other point: preregistration is not the same thing as a Registered Report. A normal OSF preregistration timestamps your planned study; a Registered Report adds journal peer review of the plan before the results exist.

If you tell me your field + study design (e.g., “2×2 randomized experiment with a survey outcome” or “secondary analysis of an existing longitudinal dataset”), I can recommend the exact template and give you a minimal-but-rigorous preregistration checklist for it.

It's the safest general-purpose choice: OSF describes it as its standard, comprehensive template, and it remains the most broadly applicable option.

If you're doing psychology

I'd actually consider PRP-QUANT the better default for a conventional quantitative psychology paper. It's specifically intended for quantitative psychological studies, and the APA describes its newer preregistration standards as deliberately thorough and designed to encourage detailed upfront planning.

The important distinction

Don't choose based solely on the statistical test. For example, an ANOVA vs. regression isn't usually enough reason to use different templates. Choose based on what creates distinctive researcher degrees of freedom:

When choosing a preregistration template, the "best" option depends entirely on your study design, methodological complexity, and how much granular detail you need to lock in. Most researchers turn to the standardized formats hosted on the Open Science Framework (OSF) Registrations or AsPredicted.

The top template sets categorized by common study designs include:

1. Standard Experimental & Behavioral Studies
   • AsPredicted Template: The gold standard for quick, straightforward lab or online experiments (e.g., simple ANOVAs, t-tests, or basic psych surveys). It uses a concise 8-question format covering hypotheses, data collection stopping rules, variables, and exclusions. Ideal if you want a streamlined, highly readable document.
   • OSF Preregistration (Standard): A comprehensive, general-purpose quantitative template. It is more thorough than AsPredicted, walking you step-by-step through hypotheses, experimental design plans, sampling plans, and variable transformations. Best for first-time users doing complex experimental work who need explicit prompts.
2. Replications
   • Replication Recipe (OSF): Tailored specifically for direct or conceptual replications. It prompts you to clearly define the original study's effect size, exact deviations from the original protocol (if any), and how success/failure of the replication will be statistically evaluated.
3. Secondary Data Analysis & Existing Datasets
   • Secondary Data Preregistration Template: Because traditional templates assume data has not been collected yet, secondary data templates focus heavily on confirming that the researchers have not yet looked at the specific variables or subset of data answering the research question. It documents data access paths, pre-existing cleaning steps, and planned restrictions.
4. Systematic Reviews & Meta-Analyses
   • Generalized Systematic Review / PRISMA-compliant Templates: Geared toward synthesizing existing literature. These templates focus on search strings, database selection, inclusion/exclusion criteria, dual-coder reliability, and statistical synthesis (meta-analytic models) rather than human subject sampling.
5. Qualitative & Mixed-Methods Research
   • Qualitative Preregistration Template: Adapted specifically for qualitative or inductive designs (e.g., thematic analysis, ethnography, grounded theory) where rigid statistical analysis plans or hypotheses do not apply. It emphasizes sampling saturation strategies, coding frameworks, and reflexive procedures.
6. Specialized Neuroimaging & Electrophysiology
   • fMRI / EEG/ERP Preregistration Templates: Specialized frameworks addressing spatial smoothing parameters, coordinate spaces, artifact rejection criteria, and multi-voxel pattern analysis pipelines that generic psychological templates miss.

If you'd like to narrow this down, tell me:

• What is your specific study design (e.g., randomized experiment, qualitative interviews, secondary data)?
• Are you planning to register on OSF, AsPredicted , or submit as a Registered Report?

I can help you pick the exact schema or draft your responses for a section.

For a preregistration template set that covers most common study designs, I’d use OSF Registries as the backbone, with a few specialized templates for cases where the generic form is a poor fit. OSF provides a broad set of templates, including general quantitative, qualitative, secondary-data, systematic review, simulation, replication, and method-specific forms.

Recommended template set

If you want a lab-wide default policy

A practical three-template stack:

1. OSF Preregistration → default for ~80% of studies.
2. AsPredicted → quick preregistration for straightforward confirmatory studies.
3. Specialized OSF templates → whenever the design has unusual features (qualitative, secondary data, reviews, simulations, EEG, replications).

A good rule of thumb: choose the most specific template that fits your design, but don’t force a specialized template when the generic OSF form already captures your decisions clearly.

One additional distinction: a normal preregistration is a timestamped record of your planned methods and analyses; a Registered Report adds journal peer review before results are known.

Choosing the "best" preregistration template depends heavily on your specific study design. Platforms like the Center for Open Science OSF Guides and AsPredicted offer standardized frameworks tailored to different methodological workflows.

The top template sets mapped to common study designs include:

• Standard / General Experimental Designs (Lab experiments, randomized psychological or behavioral studies):
  • Best choice: AsPredicted or OSF Standard Preregistration.
  • Why: AsPredicted uses a fast, highly streamlined 8-question format covering hypotheses, data collection rules, variables, and exclusions. The OSF Standard Preregistration template provides a more exhaustive, granular breakdown of hypotheses, methods, and analysis plans for first-timers needing extra guidance.
• Secondary / Existing Data Analysis (Working with archival, open-access, or pre-collected datasets):
  • Best choice: Preregistration for Studies with Existing Data (OSF).
  • Why: Standard templates assume data has not been collected yet. This specialized template explicitly documents your current degree of familiarity with the dataset and what steps you are taking to prevent biased or p-hacked confirmatory analyses.
• Qualitative and Mixed-Methods Research (Interviews, ethnography, case studies):
  • Best choice: Qualitative Preregistration Template (Haven et al.) available on OSF.
  • Why: Traditional templates fail to fit flexible qualitative designs. This framework adapts by focusing on researcher positioning, epistemological assumptions, coding frameworks, and audit/credibility strategies rather than fixed statistical power calculations.
• Systematic Reviews and Meta-Analyses:
  • Best choice: Generalized Systematic Review / PRISMA-P-aligned Template.
  • Why: Focuses heavily on search strings, database interfaces, explicit inclusion/exclusion criteria, and screening protocols rather than human subject recruitment or experimental manipulations.
• Replication Studies:
  • Best choice: Replication Recipe (Pre-Study).
  • Why: Walks you through mapping exact methodological fidelity to the original study and pre-specifying your evaluative criteria for a successful replication.

If you share your specific study design (e.g., cross-sectional survey, RCT, qualitative interview study) and whether you already have access to the data , I can point you directly to the ideal template and key questions to focus on.

If you mean preregistration templates by study design, my default recommendation is OSF’s template set. It has a broad collection of design-specific forms, and OSF currently describes its standard OSF Preregistration as the most commonly used general-purpose option.

Best template by common design

OSF lists all of these templates—including the specialized EEG/ERP, eye-tracking, secondary-data, qualitative, simulation, replication, and systematic-review forms.

My practical ranking

1. OSF Preregistration — best overall. Use this unless your study clearly belongs to one of the specialized categories above. It's comprehensive and forces you to nail down hypotheses, variables, exclusions, sample size, and analyses before looking at the data.

2. AsPredicted — best for simple experiments. Its eight-question format asks about whether data have already been collected, the hypothesis, dependent variables, conditions, analyses, exclusion rules, sample size, and anything else worth preregistering.

3. Specialized OSF templates — best when the methodology itself matters. For example, I would use the secondary-data template rather than trying to retrofit a generic preregistration to an existing dataset.

One important point: the quality of the preregistration matters more than the platform/template. OSF specifically recommends making analysis decisions before seeing the data, stating precise exclusion rules, specifying model/covariate choices, defining outcomes, and anticipating contingencies.

If you tell me your study design (e.g., 2×2 experiment, longitudinal observational study, survey, secondary-data analysis, RCT, meta-analysis), I can recommend the exact template and give you a field-by-field preregistration checklist.

The "best" preregistration template depends heavily on your specific study design, disciplinary norms, and how granular you want your analysis plan to be. The Center for Open Science and the Open Science Framework (OSF) host the most widely adopted suite of standardized templates.

The top template sets categorized by common study designs include:

• AsPredicted (Streamlined / General)
  • Best for: Fast, straightforward, or first-time preregistrations (especially in behavioral and social sciences).
  • Why use it: It distills a study plan into 8 core, punchy questions covering hypotheses, data collection stopping rules, variables, and exclusions. It's easy to read at a glance and takes under an hour to complete. Access it directly via AsPredicted.
• OSF Preregistration (Standard / Comprehensive)
  • Best for: Confirmatory experimental designs, lab studies, and quantitative surveys requiring rigorous, exhaustive documentation.
  • Why use it: Often called the "Standard, comprehensive, and general purpose preregistration form", it walks you through detailed sections on sampling plans, variables, blinding, and analytical pipelines. Available directly on the OSF Registries Guide.
• Preregistration in Social Psychology (van 't Veer & Giner-Sorolla)
  • Best for: Social and cognitive psychology experiments, multi-condition designs, or interaction-heavy hypotheses.
  • Why use it: Explicitly prompts for manipulation checks, conditional hypotheses, and specific data-exclusion rules that generic forms might gloss over.
• Secondary / Existing Data Preregistration
  • Best for: Studies analyzing pre-existing datasets where data collection has happened, but you haven't yet looked at the specific variables/hypotheses of your current research question.
  • Why use it: It helps separate confirmatory analyses from exploratory data dredging, proving you didn't peek at the variables beforehand.
• Qualitative Preregistration (Haven et al.)
  • Best for: Interview studies, ethnographies, qualitative content analysis, or case studies.
  • Why use it: Traditional templates assume quantitative metrics, p-values, and sample size power calculations. The qualitative variant focuses instead on sampling saturation, coding frameworks, and reflexivity.
• Replication Recipe (Brandt et al.)
  • Best for: Direct or conceptual replications of published work.
  • Why use it: Tailored specifically to document deviations from the original methodology (e.g., sample shifts, translated materials, or updated apparatuses) alongside the targeted effect sizes.

If you tell me your specific study design (e.g., cross-sectional survey, RCT, qualitative interviews, secondary data analysis), I can recommend which exact template will give you the best protection against bias while minimizing paperwork.