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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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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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Participant Adherence 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/projectid, subject_id
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.
genderString20RequiredSex of the subjectM;FM = Male; F = Female
paq_01IntegerRecommendedQue 1 checks how often patient taken anti depressant medication the last week1::51=Has taken no antidepressant medication (missed all 7 days); 2=Has taken antidepressant medication about 25% of the time (missed 5-6 days); 3=Has taken antidepressant medication about 50% of the time (missed 3-4 days); 4=Has taken antidepressant medication about 75% of the time (missed 1-2 days); 5=Has taken antidepressant medication everyday
paq_02IntegerRecommendedQue 2 record changes0;10=No; 1=Yes
paq_02_aIntegerRecommendedQue 2a stopped taking0;10=No; 1=Yesl_stop
paq_02_a1IntegerRecommendedstopped meds days agol_days
paq_02_a10IntegerRecommendedReason stopped meds: symptom increase0;10=No; 1=Yesl_stsi
paq_02_a11IntegerRecommendedReason stopped meds: symptom decrease0;10=No; 1=Yesl_stsd
paq_02_a12IntegerRecommendedReason stopped meds: out of meds0;10=No; 1=Yesl_stout
paq_02_a13IntegerRecommendedReason stopped meds: forgot0;10=No; 1=Yesl_stfg
paq_02_a14IntegerRecommendedReason stopped meds: other0;10=No; 1=Yesl_stoth
paq_02_a16IntegerRecommendedReason stopped meds: side effects0;10=No; 1=Yesl_stse
paq_02_a17IntegerRecommendedReason skipped meds: symptom increase0;10=No; 1=Yesl_sksi
paq_02_a18IntegerRecommendedReason skipped meds: symptom decrease0;10=No; 1=Yesl_sksd
paq_02_a19IntegerRecommendedReason skipped meds: out of meds0;10=No; 1=Yesl_skout
paq_02_a2IntegerRecommendedReason skipped meds: side effects0;10=No; 1=Yesl_skse
paq_02_a20IntegerRecommendedReason skipped meds: other0;10=No; 1=Yesl_skoth
paq_02_a21IntegerRecommendedReason reduced meds: side effects0;10=No; 1=Yesl_rese
paq_02_a22IntegerRecommendedReason reduced meds: symptom increase0;10=No; 1=Yesl_resi
paq_02_a23IntegerRecommendedReason reduced meds: symptom decrease0;10=No; 1=Yesl_resd
paq_02_a24IntegerRecommendedReason reduced meds: other0;10=No; 1=Yesl_reoth
paq_02_a3IntegerRecommendedReason increased meds: symptom increase0;10=No; 1=Yesl_insi
paq_02_a4IntegerRecommendedReason increased meds: symptom decrease0;10=No; 1=Yesl_insd
paq_02_a5IntegerRecommendedReason increased meds: out of meds0;10=No; 1=Yes
paq_02_a6IntegerRecommendedReason increased meds: forgot0;10=No; 1=Yes
paq_02_a7IntegerRecommendedReason increased meds: other0;10=No; 1=Yesl_inoth
paq_02_a9IntegerRecommendedReason increased meds: side effects0;10=No; 1=Yesl_inse
paq_02_bIntegerRecommendedQue 2b skipped meds0;10=No; 1=Yesl_skip
paq_02_cIntegerRecommendedQue 2c reduced meds0;10=No; 1=Yesl_reduce
paq_02_dIntegerRecommendedQue 2d Increased meds0;10=No; 1=Yesl_incmed
subject_descriptionString4,000RecommendedSubject related information (e.g the affection, phenotype, disease information, etc.).
siteString100RecommendedSiteStudy Site
weekFloatRecommendedWeek in level/study99=week 10-week 14
vis_typeIntegerRecommendedVisit type0::21=Phone; 0=doctor's office; 2=No, not phone interviewphone
masked_statusIntegerRecommendedMedication: Labeled or Masked?1;21=Labeled; 2=Masked
days_baselineIntegerRecommendedDays since baselinedate
l_msdaysIntegerRecommendedHow many days have you missed taking your study medications during the last 7 days?0::7
l_as_rxIntegerRecommendedDid you take your study medications as prescribed during the last 7 days?0;10=No; 1=Yes
l_skfgIntegerRecommendedReason skipped meds: forgot0;10=No; 1=Yes
l_reoutIntegerRecommendedReduced med dose because of: out of meds0;10=No; 1=Yes
m_msdaysIntegerRecommendedHow many days have you missed taking your masked study medications during the last 7 days?
m_as_rxIntegerRecommendedDid you take your masked study medications as prescribed during the last 7 days?0;10=No;1=Yes
m_stopIntegerRecommendedStopped taking masked med0;10=No;1=Yes
m_daysIntegerRecommendedDays ago stopped masked med
m_stseIntegerRecommendedMasked study medication stopped: Side effects0;10=No;1=Yes
m_stsiIntegerRecommendedMasked study medication stopped:Symptom increase0;10=No;1=Yes
m_stsdIntegerRecommendedMasked study medication stopped:Symptom decrease0;10=No;1=Yes
m_stoutIntegerRecommendedMasked study medication stopped:Ran out of meds0;10=No;1=Yes
m_stfgIntegerRecommendedMasked study medication stopped:Forgot to take0;10=No;1=Yes
m_stothIntegerRecommendedStopped taking masked med for some other reason0;10=No;1=Yes
m_skipIntegerRecommendedMasked study medication:Skipped taking masked med0;10=No;1=Yes
m_skseIntegerRecommendedMasked study medication skipped:Side effects0;10=No;1=Yes
m_sksiIntegerRecommendedMasked study medication skipped:Symptom increase0;10=No;1=Yes
m_sksdIntegerRecommendedMasked study medication skipped:Symptom decrease0;10=No;1=Yes
m_skoutIntegerRecommendedMasked study medication skipped:Ran out of meds0;10=No;1=Yes
m_skfgIntegerRecommendedMasked study medication skipped:Forgot to take0;10=No;1=Yes
m_skothIntegerRecommendedSkipped labeled med for other reason0;10=No;1=Yes
m_reduceIntegerRecommendedReduced masked med dose0;10=No;1=Yes
m_reseIntegerRecommendedMasked study medication reduced:Side effects0;10=No;1=Yes
m_resiIntegerRecommendedMasked study medication reduced:Symptom increase0;10=No;1=Yes
m_resdIntegerRecommendedMasked study medication reduced:Symptom decrease0;10=No;1=Yes
m_reoutIntegerRecommendedMasked study medication reduced:Ran out of meds0;10=No;1=Yes
m_reothIntegerRecommendedreduced masked med dose for other reason0;10=No;1=Yes
m_incmedIntegerRecommendedIncreased masked med dose0;10=No;1=Yes
m_inseIntegerRecommendedMasked study medication increased:Side effects0;10=No;1=Yes
m_insiIntegerRecommendedMasked study medication increased:Symptom increase0;10=No;1=Yes
m_insdIntegerRecommendedMasked study medication increased: Symptom decrease0;10=No;1=Yes
m_inothIntegerRecommendedIncreased masked med dose for other reason0;10=No;1=Yes
paq_02_a7_spString100RecommendedReason increased meds: other. Specify
paq_02_a14_spString100RecommendedReason stopped meds: other. Specify
paq_02_a24_spString100RecommendedReason reduced meds: other. Specify
paq_02_a20_spString100RecommendedReason skipped meds: other. Specify
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: paq01 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.