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Filter Cart
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Description
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Data Structures with shared data
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helpcenter.filter-cart

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.

Penn Word Memory Test

861 Shared Subjects

N/A
Clinical Assessments
Cognitive
12/21/2018
pwmt01
04/14/2021
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
interview_date Date Required Date on which the interview/genetic test/sampling/imaging/biospecimen was completed. MM/DD/YYYY
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
respondent String 20 Recommended Respondent Mother;Father;Parent;Guardian;Teacher;Child;Self;Caregiver;Partner;Other
study String 100 Recommended Study; The code for each individual study cpw_a_valid_code
Query visit String 60 Recommended Visit name
subject_description String 4,000 Recommended Subject related information (e.g the affection, phenotype, disease information, etc.). label
valid_code String 2 Recommended Notes C; F; S; V C=concern; F=flag; S=skip; V=valid
version_form String 121 Recommended Form used/assessment name cpw_form
Query cpw_cr Float Recommended CPW Total Correct Responses 0::40 cpw.iwrd_tot, cpw_a_cpw_cr
Query cpw_w_rtcr Float Recommended Weighted Median Response Time for CPW Total Correct Responses (ms) cpw.iwrd_rtc, cpw_a_cpw_w_rtcr
Query cpw_rtcr Float Recommended CPW Median Total Correct Response Time (ms) cpw_a_cpw_rtcr
Query cpw_er Integer Recommended CPW Total Incorrect Responses 0::40 cpw_a_cpw_er
Query cpw_w_rter Float Recommended CPW Weighted Median Total Incorrect Response Time (ms) cpw_a_cpw_w_rter
Query cpw_rter Float Recommended CPW Median Total Incorrect Response time (ms) cpw_a_cpw_rter
Query cpw_tp Integer Recommended CPW True Positive Reponses 0::20 cpw_a_cpw_tp
Query cpw_tn Integer Recommended CPW True Negative Responses 0::20 cpw_a_cpw_tn
Query cpw_fp Integer Recommended CPW False Positive Responses 0::20 cpw_a_cpw_fp
Query cpw_fn Integer Recommended CPW False Negative Responses 0::20 cpw_a_cpw_fn
Query cpw_tprt Float Recommended Median Response Time for CPW True Positive Responses cpw_a_cpw_tprt
Query cpw_tnrt Float Recommended Median Response Time for CPW True NegativeResponses cpw_a_cpw_tnrt
Query cpw_fprt Float Recommended Median Response Time for CPW False Positive Responses cpw_a_cpw_fprt
Query cpw_fnrt Float Recommended Median Response Time for CPW False Negative Responses cpw_a_cpw_fnrt
Query cpw_rt Float Recommended CPW Median Total Response Time (ms) cpw_a_cpw_rt
Query cpw_lrsr Integer Recommended CPW Longest Run of Same Responses 0::40
Query cpw_lrsr_200 Integer Recommended CPW Longest Run of Same Responses under 200 (ms) 0::40
Query cpw_cnt_200 Integer Recommended CPW Total Count under 200 (ms) 0::40
Query pwmt_seen1 Integer Recommended Participant rating of words seen before: Word 1 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_seen2 Integer Recommended Participant rating of words seen before: Word 2 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_seen3 Integer Recommended Participant rating of words seen before: Word 3 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_seen4 Integer Recommended Participant rating of words seen before: Word 4 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_seen5 Integer Recommended Participant rating of words seen before: Word 5 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_seen6 Integer Recommended Participant rating of words seen before: Word 6 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_seen7 Integer Recommended Participant rating of words seen before: Word 7 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_seen8 Integer Recommended Participant rating of words seen before: Word 8 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_seen9 Integer Recommended Participant rating of words seen before: Word 9 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_seen10 Integer Recommended Participant rating of words seen before: Word 10 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_seen11 Integer Recommended Participant rating of words seen before: Word 11 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_seen12 Integer Recommended Participant rating of words seen before: Word 12 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_seen13 Integer Recommended Participant rating of words seen before: Word 13 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_seen14 Integer Recommended Participant rating of words seen before: Word 14 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_seen15 Integer Recommended Participant rating of words seen before: Word 15 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_seen16 Integer Recommended Participant rating of words seen before: Word 16 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_seen17 Integer Recommended Participant rating of words seen before: Word 17 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_seen18 Integer Recommended Participant rating of words seen before: Word 18 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_seen19 Integer Recommended Participant rating of words seen before: Word 19 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_seen20 Integer Recommended Participant rating of words seen before: Word 20 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_distractor1 Integer Recommended Participant rating of distractor words: Word 1 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_distractor2 Integer Recommended Participant rating of distractor words: Word 2 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_distractor3 Integer Recommended Participant rating of distractor words: Word 3 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_distractor4 Integer Recommended Participant rating of distractor words: Word 4 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_distractor5 Integer Recommended Participant rating of distractor words: Word 5 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_distractor6 Integer Recommended Participant rating of distractor words: Word 6 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_distractor7 Integer Recommended Participant rating of distractor words: Word 7 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_distractor8 Integer Recommended Participant rating of distractor words: Word 8 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_distractor9 Integer Recommended Participant rating of distractor words: Word 9 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_distractor10 Integer Recommended Participant rating of distractor words: Word 10 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_distractor11 Integer Recommended Participant rating of distractor words: Word 11 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_distractor12 Integer Recommended Participant rating of distractor words: Word 12 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_distractor13 Integer Recommended Participant rating of distractor words: Word 13 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_distractor14 Integer Recommended Participant rating of distractor words: Word 14 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_distractor15 Integer Recommended Participant rating of distractor words: Word 15 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_distractor16 Integer Recommended Participant rating of distractor words: Word 16 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_distractor17 Integer Recommended Participant rating of distractor words: Word 17 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_distractor18 Integer Recommended Participant rating of distractor words: Word 18 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_distractor19 Integer Recommended Participant rating of distractor words: Word 19 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
Query pwmt_distractor20 Integer Recommended Participant rating of distractor words: Word 20 0::4 0 = Definitely not; 1 = Probably not; 2 = Probably yes; 3 = Definitely yes
cpwd_a_dwrd_tot Integer Recommended Penn Word Memory Test Delayed Memory- CPWD Total Correct Response 0::40 cpwd_a.dwrd_tot
cpwd_a_dwrd_rtc Float Recommended Penn Word Memory Test Delayed Memory- Median Reaction Time for CPWD Total Correct Responses (ms) cpwd_a.dwrd_rtc
cpw_a_cpw_dn Integer Recommended Total number of times the Definitely No response option was chosen
cpw_a_cpw_py Integer Recommended Total number of times the Probably Yes response option was chosen
cpw_a_cpw_pn Integer Recommended Total number of times the Probably No response option was chosen
cpw_a_cpw_dy Integer Recommended Total number of times the Definitely Yes response option was chosen
word_memory_test Integer Recommended Was the Word Memory Test completed? 1::3 1 = Completed; 2 = Not Completed; 3 = Other
reason_explanation_word String 150 Recommended Reason/Explanation for not completing the Word Memory Test
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.