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Filter Cart

Viewable at the top right of NDA pages, the Filter Cart is a temporary holder for filters and data they select. Filters are added to the Workspace first, before being submitted to The Filter Cart. Data selected by filters in the Filter Cart can be added to a Data Package or an NDA Study from the Data Packaging Page, by clicking the 'Create Data Package / Add Data to Study' button.

The filter cart supports combining multiple filters together, and depending on filter type will use "AND" or "OR"  when combining filters.

Multiple selections from the same filter type will result in those selections being applied with an ‘OR’ condition. For example, if you add an NDA Collection Filter with selections for both collections 2112 and 2563 to an empty Workspace, the subjects from NDA Collection 2112 ‘OR’ NDA Collection 2563 will be added to your Workspace even if a subject is in both NDA Collections. You can then add other NDA Collections to your Workspace which further extends the ‘OR’ condition.

If a different filter type is added to your Workspace, or a filter has already been submitted to the Filter Cart, the operation then performs a logical ‘AND’ operation. This means that given the subjects returned from the first filter, only those subjects that matched the first filter are returned by the second filter (i.e., subjects that satisfied both filters).

When combining other filters with the GUID filter, please note the GUID filter should be added last. Otherwise, preselected data may be lost. For example, a predefined filter from Featured Datasets may select a subset of data available for a subject. When combined with a GUID filter for the same subject, the filter cart will contain all data available from that subject, data structure, and dataset; this may be more data than was selected in the predefined filter for that subject. Again, you should add the GUID Filter as the last filter to your cart. This ensures 'AND' logic between filters and will limit results to the subjects, data structures, and datasets already included in your filter cart.

Note that only the subjects specific to your filter will be added to your Filter Cart and only on data shared with the research community. Other data for those same subjects may exist (i.e., within another NDA Collection, associated with a data structure that was not requested in the query, etc.). So, users should select ‘Find all Subjects Data’ to identify all data for those specific subjects. 

Additional Tips:

  • You may query the data without an account, but to gain access you will need to create an NDA user account and apply for access.  Most data access requires that you or your lab are sponsored by an NIH recognized institution with Federal Wide Assurance (FWA).  Without access, you will not be able to obtain individual-level data. 

    Once you have selected data of interest you can:
  • Create a data package - This allows you to specify format for access/download
  • Assign to Study Cohort - Associate the data to an NDA Study allowing for a DOI to be generated and the data to be linked directly to a finding, publication, or data release. 
  • Find All Subject Data - Depending on filter types being used, not all data associated with a subject will be selected.  Data may be restricted by data structure, NDA Collection, or outcome variables (e.g., NDA Study). ‘Find All Data’ expands the fliter criteria by replacing all filters in your Filter Cart with a single Query by GUID filter for all subjects selected by those filters.

    Please Note:
  • When running a query, it may take a moment to populate the Filter Cart. Queries happen in the background so you can define other queries during this time. 
  • When you add your first filter, all data associated with your query will be added to the Filter Cart (e.g., a Concept, an NDA Collection, a Data Structure/Element, etc.). As you add additional filters, they will also display in the Filter Cart. Only the name of filter will be shown in the Filter Cart, not the underlying structures. 
  • Information about the contents of the Filter Cart can be seen by clicking "Edit”.
  • Once your results appear in the Filter Cart, you can create a data package or assign subjects to a study by selecting the 'Package/Assign to Study' option. You can also 'Edit' or 'Clear' filters.

Frequently Asked Questions

  • The Filter Cart currently employs basic AND/OR Boolean logic. A single filter may contain multiple selections for that filter type, e.g., a single NDA Study filter might contain NDA Study 1 and NDA Study 2. A subject that is in EITHER 1 OR 2 will be returned.  Adding multiple filters to the cart, regardless of type, will AND the result of each filter.  If NDA Study 1 and NDA Study 2 are added as individual filters, data for a subject will only be selected if the subject is included in  BOTH 1 AND 2.

    When combining other filters with the GUID filter, please note the GUID filter should be added last. Otherwise, preselected data may be lost. For example, a predefined filter from Featured Datasets may select a subset of data available for a subject. When combined with a GUID filter for the same subject, the filter cart will contain all data available from that subject, data structure, and dataset; this may be more data than was selected in the predefined filter for that subject. Again, you should add the GUID Filter as the last filter to your cart. This ensures 'AND' logic between filters and will limit results to the subjects, data structures, and datasets already included in your filter cart.

  • Viewable at the top right of NDA pages, the Filter Cart is a temporary holder of data identified by the user, through querying or browsing, as being of some potential interest. The Filter Cart is where you send the data from your Workspace after it has been filtered.

  • After filters are added to the Filter Cart, users have options to ‘Create a Package’ for download, ‘Associate to Study Cohort’, or ‘Find All Subject Data’. Selecting ‘Find All Subject Data’ identifies and pulls all data for the subjects into the Filter Cart. Choosing ‘Create a Package’ allows users to package and name their query information for download. Choosing ‘Associate to Study Cohort’ gives users the opportunity to choose the Study Cohort they wish to associate this data.


  • Once your filter cart contains the subjects of interest, select Create Data Package/Assign to Data Study which will provide options for accessing item level data and/or assigning to a study.  

  • Once queries have been added to your workspace, the next step is to Submit the Filters in the workspace to the Filter Cart.  This process runs the queries selected, saving the results within a filter cart attached to your account.  

  • The Workspace within the General Query Tool is a holding area where you can review your pending filters prior to adding them to Filter Cart. Therefore, the first step in accessing data is to select one or more items and move it into the Workspace. 


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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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Auditory Continuous Performance Test

368 Shared Subjects

Clinical Assessments
Task Based
View Change History
Query Element Name Data Type Size Required Description Value Range Notes Aliases
subjectkey GUID Required The NDAR Global Unique Identifier (GUID) for research subject NDAR*
src_subject_id String 20 Required Subject ID how it's defined in lab/project subjectid, subjectnumber
interview_date Date Required Date on which the interview/genetic test/sampling/imaging/biospecimen was completed. MM/DD/YYYY datacollecteddate
interview_age Integer Required Age in months at the time of the interview/test/sampling/imaging. 0 :: 1260 Age 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.
sex String 20 Required Sex of subject at birth M;F; O; NR M = Male; F = Female; O=Other; NR = Not reported gender
Query auditory_q1 Integer Recommended QA-Block 1: Hit 0::18 neurocog_cpt_01
Query auditory_q2 Integer Recommended QA-Block 1: Miss 0::18 neurocog_cpt_02
Query auditory_q3 Integer Recommended QA-Block 1: False 0::50 neurocog_cpt_03
Query auditory_q4 Integer Recommended QA-Block 1: %Hits 0::100 neurocog_cpt_04
Query auditory_q5 Integer Recommended QA-Block 1: RT 300::1500 (ms) neurocog_cpt_05
Query auditory_q6 Integer Recommended Q3A-Block 1: Hit 0::12 neurocog_cpt_06
Query auditory_q7 Integer Recommended Q3A-Block 1: Miss 0::12 neurocog_cpt_07
Query auditory_q8 Integer Recommended Q3A-Block 1: False 0::50 neurocog_cpt_08
Query auditory_q9 Integer Recommended Q3A-Block 1: %Hits 0::100 neurocog_cpt_09
Query auditory_q10 Integer Recommended Q3A-Block 1: RT 300::1500 (ms) neurocog_cpt_10
Query auditory_q11 Integer Recommended Q1AINT-Block 1: Hit 0::18 neurocog_cpt_11
Query auditory_q12 Integer Recommended Q1AINT-Block 1: Miss 0::18 neurocog_cpt_12
Query auditory_q13 Integer Recommended Q1AINT-Block 1: False 0::50 neurocog_cpt_13
Query auditory_q14 Integer Recommended Q1AINT-Block 1: %Hits 0::100 neurocog_cpt_14
Query auditory_q15 Integer Recommended Q1AINT-Block 1: RT 300::1500 (ms) neurocog_cpt_15
Query auditory_q16 Integer Recommended Q3A-Block 2: Hit 0::12 neurocog_cpt_16
Query auditory_q17 Integer Recommended Q3A-Block 2: Miss 0::12 neurocog_cpt_17
Query auditory_q18 Integer Recommended Q3A-Block 2: False 0::50 neurocog_cpt_18
Query auditory_q19 Integer Recommended Q3A-Block 2: %Hits 0::100 neurocog_cpt_19
Query auditory_q20 Integer Recommended Q3A-Block 2: RT 300::1500 (ms) neurocog_cpt_20
Query auditory_q21 Integer Recommended Q1AINT-Block 2: Hit 0::18 neurocog_cpt_21
Query auditory_q22 Integer Recommended Q1AINT-Block 2: Miss 0::18 neurocog_cpt_22
Query auditory_q23 Integer Recommended Q1AINT-Block 2: False 0::50 neurocog_cpt_23
Query auditory_q24 Integer Recommended Q1AINT-Block 2: %Hits 0::100 neurocog_cpt_24
Query auditory_q25 Integer Recommended Q1AINT-Block 2: RT 300::1500 (ms) neurocog_cpt_25
Query auditory_q26 Integer Recommended QA-Block 2: Hit 0::18 neurocog_cpt_26
Query auditory_q27 Integer Recommended QA-Block 2: Miss 0::18 neurocog_cpt_27
Query auditory_q28 Integer Recommended QA-Block 2: False 0::50 neurocog_cpt_28
Query auditory_q29 Integer Recommended QA-Block 2: %Hits 0::100 neurocog_cpt_29
Query auditory_q30 Integer Recommended QA-Block 2: RT 300::1500 (ms) neurocog_cpt_30
Query auditory_t1 Integer Recommended Total Q3A-Block : Hit 0::24 neurocog_cpt_36
Query auditory_t2 Integer Recommended Total Q3A-Block : Miss 0::24 neurocog_cpt_37
Query auditory_t3 Integer Recommended Total Q3A-Block : False 0::100 neurocog_cpt_38
Query auditory_t4 Integer Recommended Total Q3A-Block : %Hits 0::100 neurocog_cpt_39
Query auditory_t5 Integer Recommended Total Q3A-Block : RT 300::1500 (ms) neurocog_cpt_40
Query auditory_t6 Integer Recommended Total QA-Block : Hit 0::36 neurocog_cpt_31
Query auditory_t7 Integer Recommended Total QA-Block : Miss 0::36 neurocog_cpt_32
Query auditory_t8 Integer Recommended Total QA-Block : False 0::100 neurocog_cpt_33
Query auditory_t9 Integer Recommended Total QA-Block : %Hits 0::100 neurocog_cpt_34
Query auditory_t10 Integer Recommended Total QA-Block : RT 300::1500 (ms) neurocog_cpt_35
Query auditory_t11 Integer Recommended Total Q1AINT-Block : Hit 0::36 neurocog_cpt_41
Query auditory_t12 Integer Recommended Total Q1AINT-Block : Miss 0::36 neurocog_cpt_42
Query auditory_t13 Integer Recommended Total Q1AINT-Block : False 0::100 neurocog_cpt_43
Query auditory_t14 Integer Recommended Total Q1AINT-Block : %Hits 0::100 neurocog_cpt_44
Query auditory_t15 Integer Recommended Total Q1AINT-Block : RT 300::1500 (ms) neurocog_cpt_45
Query site String 101 Recommended Site Study Site sitenumber
Query visit_name String 20 Recommended session ID/screening ID visitnumber
Query visit String 60 Recommended Visit name visitlabel
Query subjecttype String 20 Recommended Subject Type Control;Prodromal; Enhanced; Non-Enhanced
Query dataquality Integer Recommended Data quality 0::5 0=No data (cancelled); 1=Data entered but only once, has missing data; 2=Data entered but only once, no missing data; 3=Double entered; 4=Data frozen for cleaning; 5=Data clean/locked
Query elig_inclusion_check Integer Recommended Checks for a pass/fail on Elig for Inclusion 0::3 0=Failed (Ineligible); 1=Passed (Eligible); 2=In screening; 3=NA
Query nc_omis Integer Recommended CPT number of Ommissions Score
Query nc_comm Integer Recommended CPT number of Commissions Score
Query nc_dp Float Recommended CPT d Prime Score
Query rand_num Integer Recommended Randomization Number 0::2
Query daysrz Integer Recommended days since randomization
Query week Float Recommended Week in level/study 99=week 10-week 14
Query rtmean Float Recommended Mean Reaction Time
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.