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This is a U.S. Government computer system, which may be accessed and used only for authorized Government business by authorized personnel. Unauthorized access or use of this computer system may subject violators to criminal, civil, and/or administrative action. All information on this computer system may be intercepted, recorded, read, copied, and disclosed by and to authorized personnel for official purposes, including criminal investigations. Such information includes sensitive data encrypted to comply with confidentiality and privacy requirements. Access or use of this computer system by any person, whether authorized or unauthorized, constitutes consent to these terms. There is no right of privacy in this system.

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NIMH Data Archive
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Data Structures with shared data
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NDA Help Center

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 filter 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

  • What is a 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.
  • What do I do after filters are added to the Filter Cart?
    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.
  • Are there limitations on the amount of data a user can download?

    NDA limits the rate at which individual users can transfer data out of Amazon Web Services (AWS) S3 Object storage to non-AWS internet addresses. All users have a download limit of 20 Terabytes. This limit applies to the volume of data an individual user can transfer within a 30-day window. Only downloads to non-AWS internet addresses will be counted against the limit.

  • How does Filter Cart Boolean logic work?

    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.

Glossary

  • Workspace
    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.
  • 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 adds data using an AND condition. The opportunity to further refine data to determine what will be downloaded or sent to a miNDAR is available on the Data Packaging Page, the next step after the Filter Cart. Subsequent access to data is restricted by User Permission or Privilege; however Filter Cart use is not.
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Aggression Questionnaire

947 Shared Subjects

Defined by Dr Sukhodolsky lab at Yale Child Study Center
Clinical Assessments
Aggression
01/12/2015
aq01
03/26/2018
View Change History
01
Definition
Submission Template
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 id, subject
interview_date Date Required Date on which the interview/genetic test/sampling/imaging/biospecimen was completed. MM/DD/YYYY adate, interviewyear
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, sex
grade String 50 Recommended Current Grade lgrade
Query race String 30 Recommended Race of study subject American Indian/Alaska Native; Asian; Hawaiian or Pacific Islander; Black or African American; White; More than one race; Unknown or not reported; Other Non-White; Other
Query ethnicity String 30 Recommended Ethnicity of participant
Hispanic or Latino; Not Hispanic or Latino; Unknown
Query aq_1 Integer Recommended 1. My friends say that I argue a lot. 1::5; 999 1=not at all like me; 2=a little like me; 3=somewhat like me; 4=very much like me; 5=completely like me a1
Query aq_2 Integer Recommended 2. Other people always seem to get the breaks. 1::5; 999 1=not at all like me; 2=a little like me; 3=somewhat like me; 4=very much like me; 5=completely like me a2
Query aq_3 Integer Recommended 3. I flare up quickly, but get over it quickly. 1::5; 999 1=not at all like me; 2=a little like me; 3=somewhat like me; 4=very much like me; 5=completely like me a3
Query aq_4 Integer Recommended 4. I often find myself disagreeing with people. 1::5; 999 1=not at all like me; 2=a little like me; 3=somewhat like me; 4=very much like me; 5=completely like me a4
Query aq_5 Integer Recommended 5. At times I feel I have gotten a raw deal out of life. 1::5; 999 1=not at all like me; 2=a little like me; 3=somewhat like me; 4=very much like me; 5=completely like me a5
Query aq_6 Integer Recommended 6. I can't help getting into arguments when people disagree with me. 1::5; 999 1=not at all like me; 2=a little like me; 3=somewhat like me; 4=very much like me; 5=completely like me a6
Query aq_7 Integer Recommended 7. At times I get very angry for no god reason. 1::5; 999 1=not at all like me; 2=a little like me; 3=somewhat like me; 4=very much like me; 5=completely like me a7
Query aq_8 Integer Recommended 8. I may hit someone if he or she provokes me. 1::5; 999 1=not at all like me; 2=a little like me; 3=somewhat like me; 4=very much like me; 5=completely like me a8
Query aq_9 Integer Recommended 9. I wonder why sometimes I feel so bitter about things. 1::5; 999 1=not at all like me; 2=a little like me; 3=somewhat like me; 4=very much like me; 5=completely like me a9
Query aq_10 Integer Recommended 10. I have threatened people I know. 1::5; 999 1=not at all like me; 2=a little like me; 3=somewhat like me; 4=very much like me; 5=completely like me a10
Query aq_11 Integer Recommended 11. Someone has pushed me so far that I hit him or her. 1::5; 999 1=not at all like me; 2=a little like me; 3=somewhat like me; 4=very much like me; 5=completely like me a11
Query aq_12 Integer Recommended 12. I have trouble controlling my temper. 1::5; 999 1=not at all like me; 2=a little like me; 3=somewhat like me; 4=very much like me; 5=completely like me a12
Query aq_13 Integer Recommended 13. If I'm angry enough, I may mess up someone's work. 1::5; 999 1=not at all like me; 2=a little like me; 3=somewhat like me; 4=very much like me; 5=completely like me a13
Query aq_14 Integer Recommended 14. I have been mad enough to slam a door when leaving someone behind in the room. 1::5; 999 1=not at all like me; 2=a little like me; 3=somewhat like me; 4=very much like me; 5=completely like me a14
Query aq_15 Integer Recommended 15. When people are bossy, I take my time doing what they want, just to show them. 1::5; 999 1=not at all like me; 2=a little like me; 3=somewhat like me; 4=very much like me; 5=completely like me a15
Query aq_16 Integer Recommended 16. I wonder what people want when they are nice to me. 1::5; 999 1=not at all like me; 2=a little like me; 3=somewhat like me; 4=very much like me; 5=completely like me a16
Query aq_17 Integer Recommended 17. I have become so mad that I have broken things. 1::5; 999 1=not at all like me; 2=a little like me; 3=somewhat like me; 4=very much like me; 5=completely like me a17
Query aq_18 Integer Recommended 18. I sometimes spread gossip about people I don't like. 1::5; 999 1=not at all like me; 2=a little like me; 3=somewhat like me; 4=very much like me; 5=completely like me a18
Query aq_19 Integer Recommended 19. I am a calm person. 1::5; 999 1=not at all like me; 2=a little like me; 3=somewhat like me; 4=very much like me; 5=completely like me a19
Query aq_20 Integer Recommended 20. When people annoy me, I may tell them what I think of them. 1::5; 999 1=not at all like me; 2=a little like me; 3=somewhat like me; 4=very much like me; 5=completely like me a20
Query aq_21 Integer Recommended 21. I sometimes feel that people are laughing at me behind my back. 1::5; 999 1=not at all like me; 2=a little like me; 3=somewhat like me; 4=very much like me; 5=completely like me a21
Query aq_22 Integer Recommended 22. I let my anger show when I do not get what I want. 1::5; 999 1=not at all like me; 2=a little like me; 3=somewhat like me; 4=very much like me; 5=completely like me a22
Query aq_23 Integer Recommended 23. At times I can't control the urge to hit someone. 1::5; 999 1=not at all like me; 2=a little like me; 3=somewhat like me; 4=very much like me; 5=completely like me a23
Query aq_24 Integer Recommended 24. I get into fights more than most people. 1::5; 999 1=not at all like me; 2=a little like me; 3=somewhat like me; 4=very much like me; 5=completely like me a24
Query aq_25 Integer Recommended 25. If somebody hits me, I hit back. 1::5; 999 1=not at all like me; 2=a little like me; 3=somewhat like me; 4=very much like me; 5=completely like me a25
Query aq_26 Integer Recommended 26. I tell my friends openly when I disagree with them. 1::5; 999 1=not at all like me; 2=a little like me; 3=somewhat like me; 4=very much like me; 5=completely like me a26
Query aq_27 Integer Recommended 27. If I have to resort to violence to protect my rights, I will. 1::5; 999 1=not at all like me; 2=a little like me; 3=somewhat like me; 4=very much like me; 5=completely like me a27
Query aq_28 Integer Recommended 28. I do not trust strangers who are too friendly. 1::5; 999 1=not at all like me; 2=a little like me; 3=somewhat like me; 4=very much like me; 5=completely like me a28
Query aq_29 Integer Recommended 29. At times I feel like a bomb ready to explode. 1::5; 999 1=not at all like me; 2=a little like me; 3=somewhat like me; 4=very much like me; 5=completely like me a29
Query aq_30 Integer Recommended 30. When someone really irritates me, I might give him or her the silent treatment. 1::5; 999 1=not at all like me; 2=a little like me; 3=somewhat like me; 4=very much like me; 5=completely like me a30
Query aq_31 Integer Recommended 31. I know that "friends" talk about me behind my back. 1::5; 999 1=not at all like me; 2=a little like me; 3=somewhat like me; 4=very much like me; 5=completely like me a31
Query aq_32 Integer Recommended 32. Some of my friends think I am a hothead. 1::5; 999 1=not at all like me; 2=a little like me; 3=somewhat like me; 4=very much like me; 5=completely like me a32
Query aq_33 Integer Recommended 33. At times I am so jealous I can't think of anything else. 1::5; 999 1=not at all like me; 2=a little like me; 3=somewhat like me; 4=very much like me; 5=completely like me a33
Query aq_34 Integer Recommended 34. I like to play practical jokes. 1::5; 999 1=not at all like me; 2=a little like me; 3=somewhat like me; 4=very much like me; 5=completely like me a34
Query aq_physical_score Integer Required Physical Aggression raw score 999 = Missing phytot
Query aq_physical_tscore Integer Required Physical Aggression T score 999 = Missing phytsc
Query aq_verbal_score Integer Required Verbal Aggression raw score 999 = Missing verbtot
Query aq_verbal_tscore Integer Required Verbal Aggression T score 999 = Missing vertsc
Query aq_anger_score Integer Required Anger raw score 999 = Missing angtot
Query aq_anger_tscore Integer Required Anger T score 999 = Missing angtsc
Query aq_hostility_score Integer Required Hostility raw score 999 = Missing hosttot
Query aq_hostility_tscore Integer Required Hostility T score 999 = Missing hostsc
Query aq_indirect_score Integer Required Indirect aggression raw score 999 = Missing iatot
Query aq_indirect_tscore Integer Required Indirect aggression T score 999 = Missing indtsc
Query aq_totalscore Integer Required AQ Total raw score 999 = Missing aqtot
Query aq_tscore Integer Required AQ T score 999 = Missing aqtsc
Query site String 101 Recommended Site Study Site
Query days_baseline Integer Recommended Days since baseline
Query visit String 60 Recommended Visit name tpoint
fspgod String 70 Recommended Subject's gender OTHER describe
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.