The Psychological Science Accelerator: Call for Study Submissions (Deadline: June 20th)

The Psychological Science Accelerator (PSA), a network of 300 labs collaborating to collect large-scale international samples of psychological data, is currently accepting study proposals from all areas of psychological science. Anyone can submit a proposal, whether or not they are a member of the PSA. Our mission is to accelerate the accumulation of reliable and generalizable evidence in psychological science, reducing the distance between truth about human behavior and mental processes and our current understanding. For a full overview of the PSA, please see our pre-print introducing our policies and procedures (https://psyarxiv.com/785qu/).

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Proposed studies can test novel hypotheses or focus on the replication of previous findings, can be basic or applied in focus, and can be exploratory or confirmatory in nature. Because accepted studies will likely involve considerable use of resources, the study selection process begins with the preparation and evaluation of a Registered Report style submission by authors hoping to collect data via the PSA network. Our Study Selection Committee will conduct an initial feasibility evaluation for all proposed studies (see below for more information on this feasibility check). Studies that pass this check will be evaluated by 10 peer reviewers and ourStudy Selection Committee for final selection. We plan to accept 2-3 studies during this round of review. Selected studies will then proceed through the PSA workflow depicted in the figure below.

processfigures1_001.jpg

Please email submissions to our Director, Dr. Christopher R. Chartier, cchartie@ashland.edu. Submissions will be accepted until June 20th, 2018.

Feasibility

All feasibility decisions are made with respect to our current, and ever changing, resources. Although the PSA is comprised of hundreds of labs from around the world who have agreed to volunteer some of their resources to PSA projects, we are currently unable to accommodate all types of designs. Submissions are more likely to pass the initial feasibility check if they have the following characteristics:

  • Do not require specialized equipment (e.g., eye-tracking, EEG) or proprietary experimental software (e.g., E-Prime) to be used at the data collection sites, unless the proposing team can provide these resources to data collection labs
  • Experimental materials and analysis scripts can be shared easily and made publicly available
  • Do not require hard-to-reach samples (e.g., clinical populations). We hope to better accommodate such sampling in the future.
  • Target sample size per site is less than 150 participants
  • Target number of data collection sites is less than 150
  • Duration of an individual data collection session is less than 90 minutes
  • The likelihood and severity of risk to the participant is kept to a minimum, such that the risk is not greater than what participants would face normally and would not require special consideration or deliberation from an ethics board.

Characteristics of strong submissions

Beyond simply being feasible given current PSA resources, strong submissions will also:

  • Accurately and clearly describe literature relevant to the study’s goals and design, such that researchers unfamiliar with the subject can understand the basic concepts behind the theory/phenomenon and the purpose of the research.
  • Clearly articulate the purpose of the research, relevant research questions, and hypotheses.
  • Clearly articulate the research design, with a focus on sound methodology appropriate to the research questions, including adequate power analysis to justify sample size.
  • Provide examples of relevant material, for example websites, experimental scripts (e.g., E-prime, Inquist, OpenSesame), precise experimental design, and/or stimuli.
  • Accurately and clearly describe an analysis strategy appropriate to the research questions and design. Pilot or simulated data and working analysis scripts are ideal for clarity.
  • Make a compelling case for the importance of large-scale collaborative data collection.

Submission Format and Guidelines

The following components are required for all submissions:

  • Cover Page, including title of the study, date of the latest draft, and keywords
  • Abstract of up to 150 words
  • Main body submission text of up to 5,000 words
  • References
  • Supplementary materials

The following guidelines are intended to assist you in the preparation of your study submission to the Psychological Science Accelerator. Submissions normally include a description of the key background literature and motivation for the study, hypotheses, study procedures, proposed statistical analysis plan, a statistical power analysis, and pilot data (wherever applicable).

Introduction

A review of the relevant literature that motivates the research question and a full description of the study aims and hypotheses.

Methods

A full description of proposed sample characteristics, including criteria for data inclusion and exclusion (e.g. outlier extraction). Procedures for objectively defining exclusion criteria due to technical errors or for any other reasons must be specified, including details of how and under what conditions data would be replaced.

A description of study procedures in sufficient detail to allow another researcher to repeat the methodology exactly, without requiring further information.

Proposed analysis pipeline, including all preprocessing steps, and a precise description of all planned analyses, including appropriate correction for multiple comparisons. Specify all covariates or regressors. Specify analysis decisions that are contingent on the outcome of prior analyses.

Results

Studies involving Neyman-Pearson inference must include a statistical power analysis. Estimated effect sizes should be justified with reference to the existing literature or theory. Since publication bias overinflates published estimates of effect size, power analysis should be based on the lowest available or meaningful estimate of the effect size.

In the case of highly uncertain effect sizes, a variable sample size and interim data analysis is permissible but with inspection points stated in advance, appropriate Type I error correction for ‘peeking’ employed, and a final stopping rule for data collection outlined.

For studies involving analyses with Bayes factors, the predictions of the theory must be specified so that a Bayes factor can be calculated. Authors should indicate what distribution will be used to represent the predictions of the theory and how its parameters will be specified.  

Full descriptions must be provided of any outcome-neutral criteria that must be met for successful testing of the stated hypotheses. Such quality checks might include the absence of floor or ceiling effects in data distributions, positive controls, or other quality checks that are orthogonal to the experimental hypotheses.

Supplemental Materials

Include full questionnaires, stimuli, and materials needed to conduct the study. Pilot data can be included to establish proof of concept, effect size estimations, or feasibility of proposed methods. Simulated data and analysis scripts are ideal for clarity of the exclusion criteria and analysis plan.

These guidelines were adapted from https://osf.io/pukzy.

 

Please email submissions to our Director, Dr. Christopher R. Chartier, cchartie@ashland.edu. Submissions will be accepted until June 20th, 2018.

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