specs:
  discipline:
    text: Thaumatology
  title:
    text: 'Cabbages cast in moderation: a comparative analysis'
  authors:
    text: Littlebottom, C., Dibbler, C., & Aching, T.
  tasks_and_roles:
    text: Unspecified
  funding:
    text: Unspecified
  cois:
    text: Unspecified
  type_of_study:
    text: Unspecified
  background:
    text: Unspecified
  stages:
    text: Unspecified
  stage:
    text: Unspecified
  start_date:
    text: Unspecified
  end_date:
    text: Unspecified
  primary_research_question:
    text: Unspecified
  secondary_research_question:
    text: Unspecified
  expectations_hypotheses:
    text: Unspecified
  main_vars:
    text: Unspecified
  secondary_vars:
    text: Unspecified
  additional_vars:
    text: Unspecified
  data_origin:
    text: Unspecified
  data_bias_minimization:
    text: Unspecified
  data_amount:
    text: Unspecified
  anyware:
    text: Unspecified
  repositories:
    text: Unspecified
  preprint:
    text: Unspecified
  misc_methods_details:
    text: Unspecified
  missing_data:
    text: Unspecified
  data_validation:
    text: Unspecified
  analysis_plan:
    text: Unspecified
  criteria_for_conclusions:
    text: Unspecified
  analyst_masking:
    text: Unspecified
  misc_analysis_details:
    text: Unspecified
jstf: []
form:
  instructions:
    Intended Use:
      heading: Intended Use
      description: This Inclusive General-Purpose Registration Form is intended as
        a general-purpose registration form. The form is designed to be applicable
        across disciplines (i.e., psychology, economics, law, physics, or any other
        field) and across study types (i.e., qualitative studies, quantitative studies,
        experiments, systematic reviews, case studies, archive studies, comparative
        legal studies, or any other type of study). This form, therefore, is a fall-back
        for more specialized forms and can be used if no specialized form or registration
        platform is available. As such, if at all possible, it is recommended to avoid
        using this form and instead use a specialized form. This inclusive general-purpose
        registration form achieves that inclusiveness and general-purposeness at the
        cost of specificity and comprehensiveness. Still, if specialized forms don't
        fit for your study, this form may be a good backup.
  metadata:
    title:
      field: title
      content: Inclusive General-Purpose Registration Form
    author:
      field: author
      content: Gjalt-Jorn Peters & Szilvia Zorgo
    date:
      field: date
      content: '2021-10-03'
    comments:
      field: comments
      content: This form was heavily based on the Inclusive Systematic Review Form
        by Van den Akker et al. (2020).
    version:
      field: version
      content: '1.1'
  items:
    discipline:
      section_id: metadata
      item_id: discipline
      item_label: Discipline
      item_description: Here you can specify your discipline (e.g. law, chemistry,
        anthropology, etc).
      item_valueTemplate: string
      item_validValues: .na.character
      item_validation: .na.character
    title:
      section_id: metadata
      item_id: title
      item_label: Title
      item_description: The title of this study (at this stage, anyway).
      item_valueTemplate: string
      item_validValues: .na.character
      item_validation: .na.character
    authors:
      section_id: metadata
      item_id: authors
      item_label: Author(s) / contributor(s)
      item_description: The authors of / contributors to this study.
      item_valueTemplate: string
      item_validValues: .na.character
      item_validation: .na.character
    tasks_and_roles:
      section_id: metadata
      item_id: tasks_and_roles
      item_label: Tasks and roles
      item_description: Describe the expected tasks and roles of each author/contributor,
        for example using the Contributor Roles Taxonomy (CRediT).
      item_valueTemplate: string
      item_validValues: .na.character
      item_validation: .na.character
    funding:
      section_id: metadata
      item_id: funding
      item_label: Funding
      item_description: List the funding sources for everybody that is involved in
        this study at this stage. If the work is unfunded, please state this as such.
      item_valueTemplate: string
      item_validValues: .na.character
      item_validation: .na.character
    cois:
      section_id: metadata
      item_id: cois
      item_label: Conflicts of interest
      item_description: List any potential conflicts of interest (e.g., if there is
        a potential outcome of this study that can in any way have negative or positive
        effects for anybody involved in this study in terms of funding, prestige,
        or opportunities). If there are no conflicts of interest, please state this
        as such.
      item_valueTemplate: string
      item_validValues: .na.character
      item_validation: .na.character
    type_of_study:
      section_id: background
      item_id: type_of_study
      item_label: Type of study
      item_description: How would you describe the type of study you are (pre)registering?
      item_valueTemplate: string
      item_validValues: .na.character
      item_validation: .na.character
    background:
      section_id: background
      item_id: background
      item_label: Background
      item_description: Introduce the topic of your study, its aims, and/or provide
        a short summary of known literature and what you want to add to this literature
        with your study.
      item_valueTemplate: string
      item_validValues: .na.character
      item_validation: .na.character
    stages:
      section_id: background
      item_id: stages
      item_label: Study stages
      item_description: Indicate the stages in which you will conduct this study.
        Common stages are preparation, data collection, and analysis, but just specify
        the stages you will use using your own words.
      item_valueTemplate: string
      item_validValues: .na.character
      item_validation: .na.character
    stage:
      section_id: background
      item_id: stage
      item_label: Current study stage
      item_description: Indicate in which stage from the list you specified in the
        "Study stages" item you are at this moment (i.e., when you freeze this registration).
      item_valueTemplate: string
      item_validValues: .na.character
      item_validation: .na.character
    start_date:
      section_id: background
      item_id: start_date
      item_label: Start date
      item_description: Indicate the planned start date, or if you already started,
        the actual start date.
      item_valueTemplate: date
      item_validValues: .na.character
      item_validation: .na.character
    end_date:
      section_id: background
      item_id: end_date
      item_label: End date
      item_description: Indicate the planned end date, or if you already completed
        the study, the actual end date.
      item_valueTemplate: date
      item_validValues: .na.character
      item_validation: .na.character
    primary_research_question:
      section_id: methods
      item_id: primary_research_question
      item_label: Primary research question(s)
      item_description: List the specific questions this study is meant to answer
        (i.e., the questions that ultimately informed the decisions made when designing
        the study plans you are registering). Note that all analyses pertaining to
        primary research questions should normally be reported in the final report.
      item_valueTemplate: string
      item_validValues: .na.character
      item_validation: .na.character
    secondary_research_question:
      section_id: methods
      item_id: secondary_research_question
      item_label: Secondary research question(s)
      item_description: List additional research questions that you will examine,
        but that took less central roles in informing the study's design. Note that
        all analyses pertaining to secondary research questions should normally be
        reported in the final report (the difference is that the study's design is
        mainly geared towards answering the primary research questions).
      item_valueTemplate: string
      item_validValues: .na.character
      item_validation: .na.character
    expectations_hypotheses:
      section_id: methods
      item_id: expectations_hypotheses
      item_label: Expectations / hypotheses
      item_description: Describe any hypotheses and/or expectations you have. These
        can pertain to your research questions, the types of sources you will find,
        social and political contexts, and contextual information that you know may
        color your interpretations and decisions.
      item_valueTemplate: string
      item_validValues: .na.character
      item_validation: .na.character
    main_vars:
      section_id: methods
      item_id: main_vars
      item_label: Main variable(s) / outcome(s) / dependent variables
      item_description: List the concepts or main / dependent / outcome variables
        you are interested in. If this study concerns one or more associations, list
        the outcome variable(s) or dependent variables. If this study does not concern
        one or more associations, list the main variables of interest here.
      item_valueTemplate: string
      item_validValues: .na.character
      item_validation: .na.character
    secondary_vars:
      section_id: methods
      item_id: secondary_vars
      item_label: Secondary variable(s) / independent variable(s) / intervention(s)
        / treatment(s)
      item_description: 'If this study''s research question(s) concerns one or more
        associations or effects, list the variable(s) that theoretically cause them
        or are assumed to otherwise explain the main variable(s) / dependent variable(s)
        / outcome(s). If this is a manipulation, treatment, or intervention, make
        sure to describe it in full: that means also describing all groups, including
        any control group(s) or comparator(s). If there are no secondary variables,
        you can just state that.'
      item_valueTemplate: string
      item_validValues: .na.character
      item_validation: .na.character
    additional_vars:
      section_id: methods
      item_id: additional_vars
      item_label: Additional variable(s) / covariate(s)
      item_description: Here, list any additional variables you are interested in
        that were not included in the two lists above, such as covariates, moderators,
        or mediators. If there are no additional variables, you can just state that.
      item_valueTemplate: string
      item_validValues: .na.character
      item_validation: .na.character
    data_origin:
      section_id: methods
      item_id: data_origin
      item_label: Data origin
      item_description: 'Describe the origin of the data you will examine. Data here
        is meant as a broad term: it refers to primary or secondary data; data you
        will collect or data that already existed; data that are measurements, recordings,
        existing documents or reports. Basically, which bits of the world will you
        look at to answer your research question(s), and how will you obtain those
        bits? If your data will be sampled from a larger population, this is where
        you can describe your sampling procedure and explain why that procedure fits
        with your goals. If your study does not involve the analysis of data at all,
        you can also indicate that here (but in that case this form will probably
        mostly not be applicable).'
      item_valueTemplate: string
      item_validValues: .na.character
      item_validation: .na.character
    data_bias_minimization:
      section_id: methods
      item_id: data_bias_minimization
      item_label: Data bias minimization
      item_description: Describe whether any procedures are in place to minimize bias
        that may be introduced as data are obtained. For example, will masking be
        applied? If data will be collected by people, will they be masked from the
        implications of patterns in the data for the research questions? If data will
        be collected from people (e.g. archivists, clerks, or research participants),
        will they be masked from the researchers' expectations regarding those data?
        If data are collected by an automated procedure (e.g. scraping websites),
        will the algorithms performing the data collection be vetted by others to
        try to identity biases? If no procedures will be implemented to minimize bias,
        you can also indicate and explain that here.
      item_valueTemplate: string
      item_validValues: .na.character
      item_validation: .na.character
    data_amount:
      section_id: methods
      item_id: data_amount
      item_label: Amount of data to be collected
      item_description: Describe how much data you plan to collect. For example, here
        you can explain whether you will study one research unit (often referred to
        as a case study), study the entire population, or how much data you plan to
        collect and why. If your data consists of archival records, social media data,
        case law, or chat logs, you can explain how many data sources you will analyse.
        If you will collect qualitative data, you can describe how much you plan to
        collect. If you will conduct quantitative analyses, you can describe your
        sample size computations. In all cases, this is also where you explain why
        that amount of data is appropriate given your aims. If you have no specific
        plans for how much data you will collect, you can also explain that here.
      item_valueTemplate: string
      item_validValues: .na.character
      item_validation: .na.character
    anyware:
      section_id: methods
      item_id: anyware
      item_label: Anyware
      item_description: List the software and hardware you plan to use for the study.
        Include model/version numbers, producers, and operating systems, if applicable.
      item_valueTemplate: string
      item_validValues: .na.character
      item_validation: .na.character
    repositories:
      section_id: methods
      item_id: repositories
      item_label: Repositories
      item_description: List the repositories you will use to publish your data, materials,
        and documentation. If you do not plan to publish one or more of these, you
        can indicate and explain that here.
      item_valueTemplate: string
      item_validValues: .na.character
      item_validation: .na.character
    preprint:
      section_id: methods
      item_id: preprint
      item_label: Preprint server
      item_description: Indicate which preprint server you plan to use to publish
        the preprint from this project. If you do not plan to publish a preprint,
        you can indicate and explain that here.
      item_valueTemplate: string
      item_validValues: .na.character
      item_validation: .na.character
    misc_methods_details:
      section_id: methods
      item_id: misc_methods_details
      item_label: Miscellaneous methods details
      item_description: Here, you can describe any details that are not captured in
        the other fields in this section.
      item_valueTemplate: string
      item_validValues: .na.character
      item_validation: .na.character
    missing_data:
      section_id: analyses
      item_id: missing_data
      item_label: Missing data
      item_description: Describe how you plan to deal with missing data (e.g. observations
        that cannot go through as planned, archive materials that cannot be obtained,
        problems with recordings, missing data points, participants that drop out,
        etc).
      item_valueTemplate: string
      item_validValues: .na.character
      item_validation: .na.character
    data_validation:
      section_id: analyses
      item_id: data_validation
      item_label: Data validation
      item_description: Describe your process of ensuring that the data are correct
        and useful (e.g., identifying outliers, triangulating with other sources,
        or other methods of verifying data integrity). Also describe your criteria
        for assessing data validity and how you will deal with data violating those
        criteria.
      item_valueTemplate: string
      item_validValues: .na.character
      item_validation: .na.character
    analysis_plan:
      section_id: analyses
      item_id: analysis_plan
      item_label: Analysis plan
      item_description: Describe the specific procedure you will apply to arrive at
        an answer to the research question(s). If you distinguish analysis tiers (e.g.,
        primary and secondary analyses, or confirmatory and exploratory analyses),
        list them and indicate which procedures you plan to use for each. Also specify
        what you will do if parts of the plan cannot be properly executed.
      item_valueTemplate: string
      item_validValues: .na.character
      item_validation: .na.character
    criteria_for_conclusions:
      section_id: analyses
      item_id: criteria_for_conclusions
      item_label: Criteria for conclusions / inference criteria
      item_description: If you plan to draw your conclusions based on pre-specified
        criteria (e.g., a minimal effect size of interest, a significance level, or
        a saturation point), list these here.
      item_valueTemplate: string
      item_validValues: .na.character
      item_validation: .na.character
    analyst_masking:
      section_id: analyses
      item_id: analyst_masking
      item_label: Analyst masking
      item_description: Describe the procedure, if any, used to mask analysts (i.e.,
        the person(s) analyzing the extracted data to arrive at answers to your research
        question(s)) from the research questions, expectations, hypotheses, and/or
        specific roles of each variable in this study. If you decide to not use masked
        analysists, you can state that decision here.
      item_valueTemplate: string
      item_validValues: .na.character
      item_validation: .na.character
    misc_analysis_details:
      section_id: analyses
      item_id: misc_analysis_details
      item_label: Miscellaneous analysis details
      item_description: Here, you can describe any details that are not captured in
        the other fields in this section.
      item_valueTemplate: string
      item_validValues: .na.character
      item_validation: .na.character
  sections:
    metadata:
      section_id: metadata
      section_label: Metadata
      section_description: This section includes some metadata about the study.
    background:
      section_id: background
      section_label: Background
      section_description: In this section, you can explain why you do this study.
    methods:
      section_id: methods
      section_label: Methods
      section_description: 'In this section, you register your plans: you describe
        what your data looks like and how you plan to obtain it.'
    analyses:
      section_id: analyses
      section_label: Analyses
      section_description: In this section, you register the analyses you plan to
        conduct on the data to learn something.
  valueTemplates:
    numeric:
      identifier: numeric
      description: Any valid number
      validValues: .na.character
      default: NA
      examples: 2.3 || 643.2
      validation: is.na(VALUE) || (is.numeric(VALUE) && (length(VALUE) == 1))
      error: NAME is not numeric, or contains more than one value.
    integer:
      identifier: integer
      description: Any valid whole number
      validValues: .na.character
      default: NA
      examples: 30 || 8762
      validation: is.na(VALUE) || (is.numeric(VALUE) && (VALUE%%1==0) && (length(VALUE)
        == 1))
      error: Error about NAME here.
    string:
      identifier: string
      description: A single character value
      validValues: .na.character
      default: '""'
      examples: '"Example" || "Another example"'
      validation: is.na(VALUE) || (is.character(VALUE) && length(VALUE) == 1)
      error: Error about NAME here.
    identifier:
      identifier: identifier
      description: A single character value that must start with a letter and can
        only contain alphanumeric characters and underscores
      validValues: .na.character
      default: '""'
      examples: '"example1" || "example_2"'
      validation: grepl("[A-Za-z][A-Za-z0-9_]*", VALUE)
      error: Identifiers must start with a letter and consist only of alphanumeric
        characters and underscores.
    countrycode:
      identifier: countrycode
      description: An ISO 3166-1 alpha-2 country code
      validValues: .na.character
      default: NA
      examples: '"NL" || "HU"'
      validation: is.na(VALUE) || (VALUE %in% countryCodeList())
      error: Error about NAME here.
    categorical:
      identifier: categorical
      description: A string that has to exactly match one of the values specified
        in the "items_validValues" column of the items sheet
      validValues: .na.character
      default: NA
      examples: '{{validValues}}'
      validation: is.na(VALUE) || (VALUE %in% {{validValues}})
      error: Error about NAME here.
    date:
      identifier: date
      description: An ISO 8601 date.
      validValues: .na.character
      default: NA
      examples: '2021-03-03'
      validation: grepl("^[0-9]{4}-[0-9]{2}-[0-9]{2}$", VALUE)
      error: The specified date does not conform to the ISO 8601 standard (YYYY-MM-DD).
    string_mandatory:
      identifier: string_mandatory
      description: A single character value that cannot be empty
      validValues: .na.character
      default: '""'
      examples: '"Example" || "Another example"'
      validation: (is.character(VALUE) && length(VALUE) == 1)
      error: Error about NAME here.
config:
  initialText: Unspecified
