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Frequently Asked Questions


NDA Help Center

Filter Cart

The Filter Cart provides a way to query and access data for which you may be interested.  There are multiple places to go query and Add to Filter Cart (Sometimes called Download).  

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 add subjects, sometimes it may take a few minutes to populate.  You can continue to do other things 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 available for the subjects selected 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 available.  However, if you want to see all of the clinical and phenotype, then select, "Find All Subject Data" to see all the data avaialble for those subjects.  

when a secord or third filter is applied, an AND condition is used to determine the subjects that are exist in all filters.  If the subject does not appear in any filter, that subjects data will be excluded from your filter cart. Given the sparcity of data in the NDA, it is possible for no subjects to appear across filters.  If that happens, clear your filter cart, and start over.  

The NDA is looking to enhance query/filtering.  Until additional tools become available, it is best to package more data than you need and then package and download the data and use other tools to further restrict and analyze the data.  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



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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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Data Structures with shared data
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Attention Shaping Questionnaire



Attention Shaping Questionnaire

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
groupIntegerRecommendedStudy group1;21= Attention shaping; 2 = Control
siteString100RecommendedSiteStudy Site
edutotFloatRecommendedTotal years of education
raceString30RecommendedRace of study subjectAmerican Indian/Alaska Native; Asian; Hawaiian or Pacific Islander; Black or African American; White; More than one race; Unknown or not reported
hispanicIntegerRecommendedIs subject of Hispanic, Latino, or Spanish origin?0; 10 = No; 1 = Yes
pregrpatFloatRecommendedAverage number of groups attended during 2 weeks prior to Basic Conversation Skills (BCS) group
pregrpptFloatRecommendedAverage number of points (as part of token economy system) in groups, during 2 weeks prior to start of BCS groups
postgrpatFloatRecommendedAverage number of other groups attended in the 2 weeks after the end of the BCS group
postgrpptFloatRecommendedAverage number of participation points earned in other groups in the 2 weeks after the BCS group ends.
disorg_1IntegerRecommendedBased on Cuesta and Peralta (1995, Schizophrenia Bulletin); sum of conceptual disorganization, poor attention, and (an item added by Cuesta and Peralta) inappropriate affect
bcs1_dateDateRecommendedDate of administration of the 4 subtests of the Comprehensive Module Test for the UCLA BCS module, at pre-treatment
skill1_1IntegerRecommendedPre-treatment score for subtest for skill area 1
skill2_1IntegerRecommendedPre-treatment score for subtest for skill area 2
skill3_1IntegerRecommendedPre-treatment score for subtest for skill area 3
skill4_1IntegerRecommendedPre-treatment score for subtest for skill area 4
bcstot1IntegerRecommendedPre-treatment score for all subtests on the Comprehensive Module Test for the BCS module
disorg_2IntegerRecommendedDisorganization symptoms sum
bcs2_dateDateRecommendedDate of administration of the 4 subtests of the Comprehensive Module Test for the UCLA BCS module, at post-treatment
skill1_2IntegerRecommendedPost-treatment score for subtest for skill area 1
skill2_2IntegerRecommendedPost-treatment score for subtest for skill area 2
skill3_2IntegerRecommendedPost-treatment score for subtest for skill area 3
skill4_2IntegerRecommendedPost-treatment score for subtest for skill area 4
bcstot2IntegerRecommendedPost-treatment score for all subtests on the Comprehensive Module Test for the BCS module
bcs2minus1IntegerRecommendedPost-treatment score minus pre-treatment score (i.e., change score on the Comprehensive Module Test for the BCS module)
nmeantotalFloatRecommendedMean of minutes of total attentiveness (based on observational ratings) across all group sessions, uncorrected
nstddevtotalFloatRecommendedStandard deviation of total attentiveness ratings across all group sessions, uncorrected
cslopetotalFloatRecommendedSlope of change in total minutes of attentiveness across all groups, after first-order autoregressive component removed
crmsqtotFloatRecommendedResidual mean square from calculation of Slope of change in total minutes of attentiveness across all groups
rootmsetotFloatRecommendedRoot mean square error (RMSE) in total-minutes-of-attentiveness-per-group ratings (degree of variability of each patient from own autoregression-corrected trend line)
nmeanmeanFloatRecommendedAverage of mean attentiveness ratings (per group, per patient), uncorrected
nstddevmeanFloatRecommendedAverage of standard deviation in mean attentivness ratings across all group sessions, uncorrected.
cslopemeanFloatRecommendedSlope of change in average minutes of attentiveness across all groups, after first-order autoregressive component removed
crmsqmeanFloatRecommendedResidual mean square from calculation of Slope of change in average minutes of attentiveness across all groups
rootmsemeanFloatRecommendedRMSE in mean-attentiveness-per-group ratings (degree of variability of each patient from own autoregression-corrected trend line)
nsessmIntegerRecommendedNumber of sessions with missing (observational) attention rating data
avgmeafirst2FloatRecommendedAverage of first 2 sessions mean attentiveness ratings
avgmeanlastFloatRecommendedAverage of last 2 sessions mean attentiveness ratings
avgtotfirstFloatRecommendedAverage of first 2 sessions total minutes of attentiveness
avgtotlastFloatRecommendedAverage of last 2 sessions total minutes of attentiveness
r_attcpzFloatRecommendedPearson correlation between daily total attentiveness and total med dose (CPZ equivalent).
medosechangeIntegerRecommendedDose change0;10 = changed dose through the course of the group; 1 = did not change, constant dose through the group
meandoseFloatRecommendedMean dose of antipsychotic medication, across all groups, in chlorpromazine equivalent units
nosietotal1FloatRecommendedTotal score on Nurses Observational Scale for Inpatient Evaluation at pre-treatment
nosietotal2FloatRecommendedTotal score on Nurses Observational Scale for Inpatient Evaluation at post-treatment
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: combined01 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.