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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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Dual Span Test



Download Definition as
Download Submission Template as
Element NameData TypeSizeRequiredDescriptionValue RangeNotesAliases
subjectkeyGUIDRequiredThe NDAR Global Unique Identifier (GUID) for research subjectNDAR*guid
src_subject_idString20RequiredSubject ID how it's defined in lab/projectcatieid, id, participant_id, randid, record_id, subject_id, subjid
interview_dateDateRequiredDate on which the interview/genetic test/sampling/imaging/biospecimen was completed. MM/DD/YYYYRequired fieldbprs_doa, intvdate
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.intvage
genderString20RequiredSex of the subjectM;FM = Male; F = Female
study_idIntegerRecommendedStudy ID number46=Acute Phase; 47=Stabilization Phase
study_conditionIntegerRecommendedStudy condition to which participant was assigned1::71 = Cognitive remediation; 2 = Comparison condition; 3 = Other; 4= treatment as usual; 5= Computers first; 6= CRT first; 7=SCIT
time_pointIntegerRecommendedAssessment time point5= Screening; 10= Baseline; 21, 22, 23 = Mid-point 1, 2, 3; 30= End-of-treatment; 41, 42, 43= Follow-up1, 2, 3 etc.
days_baselineIntegerRecommendedDays since baselinedate
dualspIntegerRecommendedDual span length (i.e. lowest level -1 at which 2/3 number sequences are recalled incorrectly) minus one1::10; 9999999999 = Missing/NA
spanFloatRecommendedDual task: percentage of sequences of span-1 length correct with span recall alone0::100; 9999999999 = missing/NA
sptraFloatRecommendedDual task: percentage of sequences of span-1 length correct at span recall with tracking0::100; 9999999999 = missing/NA
seq_erIntegerRecommendedDual task: percentage of incorrect sequences in span recall with tracking where all no.s were correct but misordered0::100; 9999999999 = missing/NA
ext_erIntegerRecommendedpercent of incorrect sequences in span recall with tracking where extra no.s were added to an otherwise correct sequence0::100; 9999999999 = missing/NA
mis_erIntegerRecommendedpercent of incorrect sequences in which a single number is omitted from an otherwise correct sequence0::100; 9999999999 = missing/NA
oth_erIntegerRecommendedpercent of sequences which were incorrect due to other errors (i.e. those not included in other error variables)0::100; 9999999999 = missing/NA
tralevIntegerRecommendedDual task: tracking speed level1::20; 9999999999 = Missing/NA
track1IntegerRecommendedDual task: Percentage of time on target in first minute - tracking alone0::100; 9999999999 = missing/NA
track2IntegerRecommendedDual task: Percentage of time on target in second minute - tracking alone0::100; 9999999999 = missing/NA
track3IntegerRecommendedDual task: Percentage time on target in third minute - tracking alone0::100; 9999999999 = missing/NA
trackFloatRecommendedDual task: average percentage time on target over minutes 1, 2 and 3 - tracking alone0::100; 9999999999 = missing/NA
trspa1IntegerRecommendedDual task: percentage time on target in first 30 seconds - tracking with span recall0::100; 9999999999 = missing/NA
trspa2IntegerRecommendedDual task: percentage time on target in 2nd 30 seconds - tracking with span recall0::100; 9999999999 = missing/NA
trspa3IntegerRecommendedDual task: percentage time on target in 3rd 30 seconds - tracking with span recall0::100; 9999999999 = missing/NA
trspa4IntegerRecommendedDual task: percentage time on target in 4th 30 seconds - tracking with span recall0::100; 9999999999 = missing/NA
trspa5IntegerRecommendedDual task: percentage time on target in 5th 30 seconds - tracking with span recall0::100; 9999999999 = missing/NA
trspa6IntegerRecommendedDual task: percentage time on target in 6th 30 seonds - tracking with span recall0::100; 9999999999 = missing/NA
trsp12FloatRecommendedDual task: average of trspa1 and trspa2 (for use in observing practice effects)0::100; 9999999999 = missing/NA
trsp34FloatRecommendedDual task: average of trsap3 and trspa4 (practice effects)0::100; 9999999999 = missing/NA
trsp56FloatRecommendedDual task: average of trspa5 and trspa6 (practice effects)0::100; 9999999999 = missing/NA
trspanFloatRecommendedDual task: overall mean of percentage time on target in 6 30 second episodes of tracking with span recall0::100; 9999999999 = missing/NA
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: dsd01 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.