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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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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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Data Structures with shared data
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CBCL for ages 1.5 to 5.0 as defined by the CPEA STAART project

Download Definition as
Download Submission Template as
Element NameData TypeSizeRequiredDescriptionValue RangeNotes
subjectkeyGUIDRequiredThe NDAR Global Unique Identifier (GUID) for research subjectNDAR*
cbcl_ageIntegerRecommendedCBCL Age
cycleIntegerRecommendedTimepoint information-1 = Screener; 0 = Baseline; 97 = Taper; 98 = Withdrawal; 99 = Interim contact; Otherwise: weeks since baseline
patidString20Recommendedsrc_Subject_idA Participant ID provided by DM-STAT must be present to process form
networkString20RecommendedNetworkCPEA or STAART Network
siteString100RecommendedSiteStudy Site
cbcl_ab5_perIntegerRecommendedPercentile0 :: 100
cbcl_ab5_totalIntegerRecommendedTotal Score0 :: 38
cbcl_ab5_tscrIntegerRecommendedT Score0 :: 100
cbcl_ad5_perIntegerRecommendedPercentile0 :: 100
cbcl_ad5_totalIntegerRecommendedTotal Score0 :: 16
cbcl_ad5_tscrIntegerRecommendedT Score0 :: 100
cbcl_af5_perIntegerRecommendedPercentile0 :: 100
cbcl_af5_totalIntegerRecommendedTotal Score0::20
cbcl_af5_tscrIntegerRecommendedT Score0 :: 100
cbcl_ah5_perIntegerRecommendedPercentile0 :: 100
cbcl_ah5_totalIntegerRecommendedTotal Score0::12
cbcl_ah5_tscrIntegerRecommendedT Score0 :: 100
cbcl_at5_perIntegerRecommendedPercentile0 :: 100
cbcl_at5_totalIntegerRecommendedTotal Score0 :: 10
cbcl_at5_tscrIntegerRecommendedT Score0 :: 100
cbcl_ax5_perIntegerRecommendedPercentile0 :: 100
cbcl_ax5_totalIntegerRecommendedTotal Score0::20
cbcl_ax5_tscrIntegerRecommendedT Score0 :: 100
cbcl_er5_perIntegerRecommendedPercentile0 :: 100
cbcl_er5_totalIntegerRecommendedTotal Score0 :: 18
cbcl_er5_tscrIntegerRecommendedT Score0 :: 100
cbcl_ex5_perIntegerRecommendedPercentile0 :: 100
cbcl_ex5_totalIntegerRecommendedTotal Score0::66
cbcl_ex5_tscrIntegerRecommendedCBCL 2-5 Externalizing T Score0 :: 100
cbcl_in5_perIntegerRecommendedPercentile0 :: 100
cbcl_in5_totalIntegerRecommendedTotal Score0::66
cbcl_in5_tscrIntegerRecommendedCBCL 2-5 Internalizing T Score0 :: 100
cbcl_od5_perIntegerRecommendedPercentile0 :: 100
cbcl_od5_totalIntegerRecommendedTotal Score0::12
cbcl_od5_tscrIntegerRecommendedT Score0 :: 100
cbcl_pd5_perIntegerRecommendedPercentile0 :: 100
cbcl_pd5_totalIntegerRecommendedTotal Score0::26
cbcl_pd5_tscrIntegerRecommendedT Score0 :: 100
cbcl_sc5_perIntegerRecommendedPercentile0 :: 100
cbcl_sc5_totalIntegerRecommendedTotal Score0 :: 22
cbcl_sc5_tscrIntegerRecommendedT Score0 :: 100
cbcl_sp5_perString255RecommendedPercentileNulled value range of: 0-100 to accept outlier data
cbcl_sp5_totalString255RecommendedTotal ScoreNulled value range of: 0-14 to accept outlier data
cbcl_sp5_tscrString255RecommendedT ScoreNulled value range of: 0-100 to accept outlier data
cbcl_tp5_perIntegerRecommendedPercentile0 :: 100
cbcl_tp5_totalIntegerRecommendedTotal Score0::66
cbcl_tp5_tscrIntegerRecommendedT Score0 :: 100
cbcl_wd5_perIntegerRecommendedPercentile0 :: 100
cbcl_wd5_totalIntegerRecommendedTotal Score0 :: 16
cbcl_wd5_tscrIntegerRecommendedT Score0 :: 100
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: cs_cbcl_1_5_5_002 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.