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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). 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.

  • 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.

Glossary

  • 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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Description
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Data Structures with shared data
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Coping Interview

78 Shared Subjects

N/A
Clinical Assessments
Coping
02/06/2018
copint01
02/06/2018
View Change History
01
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
interview_date Date Required Date on which the interview/genetic test/sampling/imaging/biospecimen was completed. MM/DD/YYYY Required field adate
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. age
sex String 20 Required Sex of the subject M;F; O; NR M = Male; F = Female; O=Other; NR = Not reported gender, sex
Query copeint_well Integer Recommended How well do you think you did on the speech compared to other kids your age? 1::5 1=The Worst; 2=Not Very Well; 3=About Average; 4=Pretty Well; 5=The Best
Query copeint_stressprep Integer Recommended How stressful was it to prepare the speech, knowing that you then had to give it in front of an audience? 1::5 1=Not at all stressful; 2=A Little Stressful; 3=Somewhat Stressful; 4=Moderately Stressful; 5=Very Stressful
Query copeint_stressspeech Integer Recommended How about during the speech, how stressful was it to be giving the speech in front of the video camera and panel of experts? 1::5 1=Not at all stressful; 2=A Little Stressful; 3=Somewhat Stressful; 4=Moderately Stressful; 5=Very Stressful
Query copeint_stressmath Integer Recommended How about during the math part, how stressful was it to be doing subtraction in front of the video camera and panel of experts? 1::5 1=Not at all stressful; 2=A Little Stressful; 3=Somewhat Stressful; 4=Moderately Stressful; 5=Very Stressful
copeint_cope String 2,000 Recommended How did you cope with or handle the stress of preparing the speech and talking in front of the audience?
copeint_calmfocus String 2,000 Recommended What did you do to stay calm and focused?
Query copeint_copecalmwork Integer Recommended Pick a number from the third box, showing how well it worked (things they did to cope or stay calm and focused) 1::5 1=Did Not Work at All; 2=Worked a Little; 3=Worked Ok; 4=Worked Pretty Well; 5=Worked Great
Query copeint_deepbreath Integer Recommended Did you do things with your body like deep breathing to be calm? 0;1 0=No; 1=Yes
copeint_deepbreath_text String 2,000 Recommended Did you do things with your body like deep breathing to be calm? If yes, what did you do?
Query copeint_deepbreathwork Integer Recommended Pick a number from the third box, showing how well it worked (things with your body like deep breathing) 1::5 1=Did Not Work at All; 2=Worked a Little; 3=Worked Ok; 4=Worked Pretty Well; 5=Worked Great
Query copeint_encourthought Integer Recommended Did you tell yourself calming or encouraging thoughts to stay calm? 0;1 0=No; 1=Yes
Query copeint_encourthoughtwork Integer Recommended Pick a number from the third box, showing how well it worked (calming or encouraging thoughts) 1::5 1=Did Not Work at All; 2=Worked a Little; 3=Worked Ok; 4=Worked Pretty Well; 5=Worked Great
copeint_coperoomdo String 2,000 Recommended What did you do in there? (Ask about materials in the room if silent)
copeint_coperoomthink String 2,000 Recommended What were you thinking about (If silent, probe if thinking about how well they did, what they could have said, etc.)
copeint_coperoomfeel String 2,000 Recommended How were you feeling? (probe for sad, mad, embarassed, scared if silent)
copeint_coperoombetter String 2,000 Recommended Did you do anything in particular to make yourself feel better? Tell me everything you tried, whether it worked or not.
Query copeint_coperoombetterwork Integer Recommended Pick a number from the third box, showing how well it worked (things they did to make self feel better). 1::5 1=Did Not Work at All; 2=Worked a Little; 3=Worked Ok; 4=Worked Pretty Well; 5=Worked Great
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.