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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

Description
Value Range
Notes
Data Structures with shared data
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Auditory Continuous Performance Test

acpt

01

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Element NameData TypeSizeRequiredDescriptionValue RangeNotesAliases
subjectkeyGUIDRequiredThe NDAR Global Unique Identifier (GUID) for research subjectNDAR*
src_subject_idString20RequiredSubject ID how it's defined in lab/projectsubjectid, subjectnumber
interview_dateDateRequiredDate on which the interview/genetic test/sampling/imaging was completed. MM/DD/YYYYRequired fielddatacollecteddate
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
auditory_q1IntegerRecommendedQA-Block 1: Hit0::18neurocog_cpt_01
auditory_q2IntegerRecommendedQA-Block 1: Miss0::18neurocog_cpt_02
auditory_q3IntegerRecommendedQA-Block 1: False0::50neurocog_cpt_03
auditory_q4IntegerRecommendedQA-Block 1: %Hits0::100neurocog_cpt_04
auditory_q5IntegerRecommendedQA-Block 1: RT300::1500(ms)neurocog_cpt_05
auditory_q6IntegerRecommendedQ3A-Block 1: Hit0::12neurocog_cpt_06
auditory_q7IntegerRecommendedQ3A-Block 1: Miss0::12neurocog_cpt_07
auditory_q8IntegerRecommendedQ3A-Block 1: False0::50neurocog_cpt_08
auditory_q9IntegerRecommendedQ3A-Block 1: %Hits0::100neurocog_cpt_09
auditory_q10IntegerRecommendedQ3A-Block 1: RT300::1500(ms)neurocog_cpt_10
auditory_q11IntegerRecommendedQ1AINT-Block 1: Hit0::18neurocog_cpt_11
auditory_q12IntegerRecommendedQ1AINT-Block 1: Miss0::18neurocog_cpt_12
auditory_q13IntegerRecommendedQ1AINT-Block 1: False0::50neurocog_cpt_13
auditory_q14IntegerRecommendedQ1AINT-Block 1: %Hits0::100neurocog_cpt_14
auditory_q15IntegerRecommendedQ1AINT-Block 1: RT300::1500(ms)neurocog_cpt_15
auditory_q16IntegerRecommendedQ3A-Block 2: Hit0::12neurocog_cpt_16
auditory_q17IntegerRecommendedQ3A-Block 2: Miss0::12neurocog_cpt_17
auditory_q18IntegerRecommendedQ3A-Block 2: False0::50neurocog_cpt_18
auditory_q19IntegerRecommendedQ3A-Block 2: %Hits0::100neurocog_cpt_19
auditory_q20IntegerRecommendedQ3A-Block 2: RT300::1500(ms)neurocog_cpt_20
auditory_q21IntegerRecommendedQ1AINT-Block 2: Hit0::18neurocog_cpt_21
auditory_q22IntegerRecommendedQ1AINT-Block 2: Miss0::18neurocog_cpt_22
auditory_q23IntegerRecommendedQ1AINT-Block 2: False0::50neurocog_cpt_23
auditory_q24IntegerRecommendedQ1AINT-Block 2: %Hits0::100neurocog_cpt_24
auditory_q25IntegerRecommendedQ1AINT-Block 2: RT300::1500(ms)neurocog_cpt_25
auditory_q26IntegerRecommendedQA-Block 2: Hit0::18neurocog_cpt_26
auditory_q27IntegerRecommendedQA-Block 2: Miss0::18neurocog_cpt_27
auditory_q28IntegerRecommendedQA-Block 2: False0::50neurocog_cpt_28
auditory_q29IntegerRecommendedQA-Block 2: %Hits0::100neurocog_cpt_29
auditory_q30IntegerRecommendedQA-Block 2: RT300::1500(ms)neurocog_cpt_30
auditory_t1IntegerRecommendedTotal Q3A-Block : Hit0::24neurocog_cpt_36
auditory_t2IntegerRecommendedTotal Q3A-Block : Miss0::24neurocog_cpt_37
auditory_t3IntegerRecommendedTotal Q3A-Block : False0::100neurocog_cpt_38
auditory_t4IntegerRecommendedTotal Q3A-Block : %Hits0::100neurocog_cpt_39
auditory_t5IntegerRecommendedTotal Q3A-Block : RT300::1500(ms)neurocog_cpt_40
auditory_t6IntegerRecommendedTotal QA-Block : Hit0::36neurocog_cpt_31
auditory_t7IntegerRecommendedTotal QA-Block : Miss0::36neurocog_cpt_32
auditory_t8IntegerRecommendedTotal QA-Block : False0::100neurocog_cpt_33
auditory_t9IntegerRecommendedTotal QA-Block : %Hits0::100neurocog_cpt_34
auditory_t10IntegerRecommendedTotal QA-Block : RT300::1500(ms)neurocog_cpt_35
auditory_t11IntegerRecommendedTotal Q1AINT-Block : Hit0::36neurocog_cpt_41
auditory_t12IntegerRecommendedTotal Q1AINT-Block : Miss0::36neurocog_cpt_42
auditory_t13IntegerRecommendedTotal Q1AINT-Block : False0::100neurocog_cpt_43
auditory_t14IntegerRecommendedTotal Q1AINT-Block : %Hits0::100neurocog_cpt_44
auditory_t15IntegerRecommendedTotal Q1AINT-Block : RT300::1500(ms)neurocog_cpt_45
siteString100RecommendedSiteStudy Sitesitenumber
visit_nameString20Recommendedsession ID/screening IDvisitnumber
visitString50RecommendedVisit nameCharacter description of each type of visitvisitlabel
subjecttypeString20RecommendedSubject TypeControl;Prodromal; Enhanced; Non-Enhanced
dataqualityIntegerRecommendedData quality0::50=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
elig_inclusion_checkIntegerRecommendedChecks for a pass/fail on Elig for Inclusion0::30=Failed (Ineligible); 1=Passed (Eligible); 2=In screening; 3=NA
nc_omisIntegerRecommendedCPT number of Ommissions Score
nc_commIntegerRecommendedCPT number of Commissions Score
nc_dpFloatRecommendedCPT d Prime Score
rand_numIntegerRecommendedRandomization Number0::2
daysrzIntegerRecommendeddays since randomization
weekFloatRecommendedWeek in level/study99=week 10-week 14
rtmeanFloatRecommendedMean 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.

Distribution for DataStructure: acpt01 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.