NDA Help Center

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NDAR provides a single access to de-identified autism research data. For permission to download data, you will need an NDAR account with approved access to NDAR or a connected repository (AGRE, IAN, or the ATP). For NDAR access, you need to be a research investigator sponsored by an NIH recognized institution with federal wide assurance. See Request Access for more information.

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This is a U.S. Government computer system, which may be accessed and used only for authorized Government business by authorized personnel. Unauthorized access or use of this computer system may subject violators to criminal, civil, and/or administrative action. All information on this computer system may be intercepted, recorded, read, copied, and disclosed by and to authorized personnel for official purposes, including criminal investigations. Such information includes sensitive data encrypted to comply with confidentiality and privacy requirements. Access or use of this computer system by any person, whether authorized or unauthorized, constitutes consent to these terms. There is no right of privacy in this system.

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Selected Filters
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The filters you have selected from various query interfaces will be stored here, in the 'Filter Cart'. The database will be queried using filters added to your 'Filter Cart', when multiple filters are defined, each will be executed using 'AND' logic, so with each filter that is applied the result set gets smaller.

From the 'Filter Cart' you can inspect each of the filters that have been defined, and you also have the option to remove filters. The 'Filter Cart' itself will display the number of filters applied along with the number of subjects that are identified by the combination of those filters. For example a GUID filter with two subjects, followed by a GUID filter for just one of those subjects would return only data for the subject that is in both GUID filters.

If you have a question about the filter cart, or underlying filters please contact the help desk at The NDA Help Desk

Value Range
Data Structures with shared data
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Digit Vigilance Test



Download Definition as
Download Submission Template as
Element NameData TypeSizeRequiredDescriptionValue RangeNotes
subjectkeyGUIDRequiredThe NDAR Global Unique Identifier (GUID) for research subjectNDAR*
src_subject_idString20RequiredSubject ID how it's defined in lab/project
interview_ageIntegerRequiredAge in months at the time of the interview/test/sampling/imaging.0 :: 1260Age is rounded to chronological month. If the research participant is 15-days-old at time of interview, the appropriate value would be 0 months. If the participant is 16-days-old, the value would be 1 month.
interview_dateDateRequiredDate on which the interview/genetic test/sampling/imaging/biospecimen was completed. MM/DD/YYYYRequired field
genderString20RequiredSex of the subjectM;FM = Male; F = Female
version_formString100RequiredForm used/assessment name
gradeString50RecommendedCurrent Grade
occupationIntegerRecommended(or OCCUP); Hollingshead Status - HEAD OF HOUSEHOLD1::91 = Farm Laborers/Menial Service Workers, Welfare Recipients; 2 = Unskilled Workers; 3 = Machine Operators, Semi-Skilled Workers; 4 = Smaller Business Owners, Skilled Manual Workers, Craftsmen, Tenant Farmers; 5 = Clerical and Sales Workers, Small Farm and Business Owners; 6 = Technicians, Semi-Professionals and Small Business Owners; 7 = Smaller Business Owners, Farm Owners, Managers, Minor Professionals; 8 = Administrators, Lesser Professionals, Proprietors of Medium-Sized Businesses; 9 = Higher Executives, Proprietors of Large Businesses, Major Professionals
handednessString29RecommendedhandednessR;L;B;999R = Right; L = Left; B = Both
p1rtime_rsIntegerRecommendedPage 1 (red) time raw score
p1rtime_ssIntegerRecommendedPage 1 (red) time scaled score
p1rtime_tsIntegerRecommendedPage 1 (red) time T score
p1rtime_pcFloatRecommendedPage 1 (red) time percentile
p2btime_rsIntegerRecommendedPage 2 (blue) time raw score
p2btime_ssIntegerRecommendedPage 2 (blue) time scaled score
p2btime_tsIntegerRecommendedPage 2 (blue) time T score
p2btime_pcFloatRecommendedPage 2 (blue) time percentile
ttime_rsIntegerRecommendedTotal time raw score
ttime_ssIntegerRecommendedTotal time scaled score
ttime_tsIntegerRecommendedTotal time T score
ttime_pcFloatRecommendedTotal time percentile
p1rtime_oessIntegerRecommendedPage 1 (red) time omission errors scaled score
p1rtime_oetsIntegerRecommendedPage 1 (red) time omission errors T score
p1rtime_oepcFloatRecommendedPage 1 (red) time omission errors percentile
p1rtime_cessIntegerRecommendedPage 1 (red) time comission errors scaled score
p1rtime_cetsIntegerRecommendedPage 1 (red) time comission errors T score
p1rtime_cepcFloatRecommendedPage 1 (red) time comission errors percentile
p1rtime_tessIntegerRecommendedPage 1 (red) time total errors scaled score
p1rtime_tetsIntegerRecommendedPage 1 (red) time total errors T score
p1rtime_tepcFloatRecommendedPage 1 (red) time total errors percentile
p2btime_oessIntegerRecommendedPage 2 (blue) time omission errors scaled score
p2btime_oetsIntegerRecommendedPage 2 (blue) time omission errors T score
p2btime_oepcFloatRecommendedPage 2 (blue) time omission errors percentile
p2btime_cessIntegerRecommendedPage 2 (blue) time comission errors scaled score
p2btime_cetsIntegerRecommendedPage 2 (blue) time comission errors T score
p2btime_cepcFloatRecommendedPage 2 (blue) time comission errors percentile
p2btime_tessIntegerRecommendedPage 2 (blue) time total errors scaled score
p2btime_tetsIntegerRecommendedPage 2 (blue) time total errors T score
p2btime_tepcFloatRecommendedPage 2 (blue) time total errors percentile
ter_rsIntegerRecommendedTotal errors raw score
ter_ssIntegerRecommendedTotal errors scaled score
ter_tsIntegerRecommendedTotal errors T score
ter_pcFloatRecommendedTotal errors percentile
data_sourceString20RecommendedSource of normative data
Data Structure

This page displays the data structure defined for the measure identified in the title and structure short name. The table below displays a list of data elements in this structure (also called variables) and the following information:

  • Element Name: This is the standard element name
  • Data Type: Which type of data this element is, e.g. String, Float, File location.
  • Size: If applicable, the character limit of this element
  • Required: This column displays whether the element is Required for valid submissions, Recommended for valid submissions, Conditional on other elements, or Optional
  • Description: A basic description
  • Value Range: Which values can appear validly in this element (case sensitive for strings)
  • Notes: Expanded description or notes on coding of values
  • Aliases: A list of currently supported Aliases (alternate element names)
  • For valid elements with shared data, on the far left is a Filter button you can use to view a summary of shared data for that element and apply a query filter to your Cart based on selected value ranges

At the top of this page you can also:

  • Use the search bar to filter the elements displayed. This will not filter on the Size of Required columns
  • Download a copy of this definition in CSV format
  • Download a blank CSV submission template prepopulated with the correct structure header rows ready to fill with subject records and upload

Please email the The NDA Help Desk with any questions.

Distribution for DataStructure: divitest01 and Element:
Chart Help

Filters enable researchers to view the data shared in NDA before applying for access or for selecting specific data for download or NDA Study assignment. For those with access to NDA shared data, you may select specific values to be included by selecting an individual bar chart item or by selecting a range of values (e.g. interview_age) using the "Add Range" button. Note that not all elements have appropriately distinct values like comments and subjectkey and are not available for filtering. Additionally, item level detail is not always provided by the research community as indicated by the number of null values given.

Filters for multiple data elements within a structure are supported. Selections across multiple data structures will be supported in a future version of NDA.