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Filter Cart

The Filter Cart provides a powerful way to query and access data for which you may be interested.  

A few points related to the filter cart are important to understand with the NDA Query/Filter implementation: 

First, the filter cart is populated asyncronously.  So, when you run a query, it may take a moment to populate but this will happen in the background so you can define other queries during this time.  

When you are adding your first filter, all data associated with your query will be added to the filter cart (whether it be a collection, a concept, a study, a data structure/elment or subjects). Not all data structures or collections will necessarily be displayed.  For example, if you select the NDA imaging structure image03, and further restrict that query to scan_type fMRI, only fMRI images will appear and only the image03 structure will be shown.  To see other data structures, select "Find All Subject Data" which will query all data for those subjects. When a secord or third filter is applied, an AND condition is used.  A subject must exist in all filters.  If the subject does not appear in any one filter, that subjects data will not be included in your filter cart. If that happens, clear your filter cart, and start over.  

It is best to package more data than you need and access those data using other tools, independent of the NDA (e.g. miNDAR snapshot), to limit the data selected.  If you have any questions on data access, are interested in using avaialble web services, or need help accessing data, please contact us for assistance.  

Frequently Asked Questions

Glossary

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NDA provides a single access to de-identified autism research data. For permission to download data, you will need an NDA account with approved access to NDA or a connected repository (AGRE, IAN, or the ATP). For NDA 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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Data Structures with shared data
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Cognitive Generalization Task

coggen

01

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_dateDateRequiredDate on which the interview/genetic test/sampling/imaging/biospecimen was completed. MM/DD/YYYYRequired field
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.
sexString20RequiredSex of the subjectM;FM = Male; F = Femalegender
mssessIntegerRecommendedSession number this measure was based on0::26 ; 550 = Pre; 1 = Session 1; 2 = Session 2; 3 = Session 3; 4 = Session 4; 5 = Session 5; 6 = Session 6; 7 = Session 7; 8 = Session 8; 9 = Session 9; 10 = Session 10; 11 = Session 11; 12 = Session 12; 13 = Session 13; 14 = Session 14; 15 = Session 15; 16 = Session 16; 17 = Session 17; 18 = Session 18; 19 = Session 19; 20 = Session 20; 21 = Session 21; 22 = Session 22; 23 = Session 23; 24 = Session 24; 25 = Session 25; 26 = Session 26; 55 = Postprctsess, proctsess
cctscenanumIntegerRecommendedScenario A number presented to subject1::6 ; -91 = Scenario 1; 2 = Scenario 2; 3 = Scenario 3; 4 = Scenario 4; 5 = Scenario 5; 6 = Scneario 6; -9 = missing or not reported
cctscenathinkString250RecommendedScenario A. If you were in this situation: what would you think
cctscenafeelString200RecommendedScenario A. If you were in this situation, what would you feel
cctscenarespString250RecommendedScenario A. If you were in this situation, how would you respond
cctscenbnumIntegerRecommendedScenario B number presented to subject1::6 ; -91 = Scenario 1; 2 = Scenario 2; 3 = Scenario 3; 4 = Scenario 4; 5 = Scenario 5; 6 = Scneario 6; -9 = missing or not reported
cctscenbthinkString200RecommendedScenario B. If you were in this situation: what would you think
cctscenbfeelString250RecommendedScenario B. If you were in this situation, what would you feel
cctscenbrespString200RecommendedScenario B. If you were in this situation, how would you respond
cctsapp_mindString5RecommendedIn the last 24 hours, have the contents covered in your therapy sessions to date come to mindTrue; False; -9True = content have come to mind; False = comments have not come to mind; -9 = missing or not recorded
cctsapp_mindtimesString20RecommendedHow many times: contents covered in your therapy sessions to date come to mindtext response; -7 = N/A as contents did not come to mind; -9 = missing or not reported
cctsapp_mindwhatString200RecommendedIn the past 24 hours, did you get to apply any of the contents covered in your therapy sessions or used the skills you have been learning during therapytext response; -7 = N/A as contents did not come to mind; -9 = missing or not reported
cctsapp_applyString20RecommendedIn the past 24 hours, did you get to apply any of the contents covered in your therapy sessions or used the skills you have been learning during therapyTrue; False;-9True = content have come to mind; False = comments have not come to mind; -9 = missing or not recorded
cctsapp_applywhatString200RecommendedSkills learned during therapy: what did you applytext response; -7 = N/A as it did not apply; -9 = missing or not reported
cctsapp_confidenceIntegerRecommendedHow confident do you feel about remembering the contents of therapy0; 10; 20; 30; 40; 50; 60; 70; 80;90; 100; -9On a likert scale: 0 = 0% (cannot at all); 10 = 10%; 20 = 20%; 30 = 30%; 40 = 40%; 50 = 50%(certain); 60 = 60%; 70 = 70%; 80 = 80%; 90 = 90%; 100 = 100%(highly certain); -9 = missing or not reported
cctsapp_usingIntegerRecommendedHow confident do you feel about using the skills you have been learning during therapy0; 10; 20; 30; 40; 50; 60; 70; 80;90; 100; -9On a likert scale: 0 = 0% (cannot at all); 10 = 10%; 20 = 20%; 30 = 30%; 40 = 40%; 50 = 50%(certain); 60 = 60%; 70 = 70%; 80 = 80%; 90 = 90%; 100 = 100%(highly certain); -9 = missing or not reported
prctcrhrFloatRecommendedCummulative recall of treatment points hard rating0::100proctcrhr
prctcrerFloatRecommendedCummulative recall of treatment points easy rating0::100proctcrer
prctlsrhrFloatRecommendedRecall of treatment points hard rating0::100proctlsrhr
prctlsrerFloatRecommendedCummulative recall of treatment points easy rating0::100proctlsrer
prctrespString100RecommendedList of treatment points remembered by partcipant from the beginning of study> = treatment point touched in most recent sessionproctresp
version_formString100RequiredForm used/assessment name
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: coggen01 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.