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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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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

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COINS Pre and Post Scan Questionnaire



Download Definition as
Download Submission Template as
Element NameData TypeSizeRequiredDescriptionValue RangeNotesAliases
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
prescan_001FloatRecommendedHow many cups of coffee (and/or other highly caffeinated drinks like Red Bull, Jolt, etc.) did you drink during the last 3 hours?
prescan_002FloatRecommendedWhat is the average number of cups of coffee (and/or other highly caffeinated drinks like Red Bull, Jolt, etc.) per day for the past week?
prescan_003IntegerRecommendedHow many cigarettes did you smoke during the last 8 hours?
prescan_004FloatRecommendedHow many hours (minutes) has it been since your last cigarette? (Please enter the unit, hours or minutes.)
prescan_004aIntegerRecommendedUnit since your last cigarette
1=Minutes;2=Hours;-999=Don�t know/Missing Data
prescan_005FloatRecommendedHow many hours did you sleep last night
prescan_006FloatRecommendedWhat is the average number of hours you slept per night during the past week?
prescan_007IntegerRecommendedDid you take any medication or any drugs during the past 24 hours?0=No;1=Yes;-999=Don't know/Missing Data
prescan_008IntegerRecommendedHave you consumed alcohol in the last 24 hours?
prescan_008bFloatRecommendedIf yes, how much alcohol in the last 24 hours?
post_1IntegerRecommendedWhich part of the experiment did you find more difficult the look trials in which you had to ignore the auditory number, or the hear trials in which you had to ignore the visual numbers on the screen
1=Look;2=Hear;3=Neither;-999=Don't Know/ Missing Data
post_2IntegerRecommendedDid you use the look cues to help you focus on the number on the screen?
0=No;1=Yes;-999=Don't Know/Missing Data
post_3IntegerRecommendedDid you use the hear cues to help you focus on the numbers on the headphones?
0=No;1=Yes;-999=Don't Know/Missing Data
post_4IntegerRecommendedIs it generally easier for you to process and remember information you see or that you hear?
1=See;2=Hear;3=Neither;-999=Don't Know/Missing Data
comments_miscString4,000RecommendedMiscellaneous comments on study, interview, methodology relevant to this form datapost_5
prescan_004bFloatRecommendedCO measurment
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: prepost_scan01 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.