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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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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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Wechsler Preschool and Primary Scale of Intelligence IV Edition

1,050 Shared Subjects

N/A
Clinical Assessments
Cognitive
05/07/2015
wppsiiv01
06/11/2020
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 subject, subject_id
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.
interview_date Date Required Date on which the interview/genetic test/sampling/imaging/biospecimen was completed. MM/DD/YYYY
sex String 20 Required Sex of subject at birth M;F; O; NR M = Male; F = Female; O=Other; NR = Not reported gender
Query wppsi_viq_pr Float Recommended Percentile Rank Percentile - Verbal
Query wppsi_piq_pr Integer Recommended Percentile RankPercentile Rank Percentile - Performance
Query wppsi_psd_pr Float Recommended Percentile Rank Percentile - Processing Speed
Query wppsi_fiq_pr Float Recommended Percentile Rank
Query wppsi_fr_pr Float Recommended Percentile - Fluid Reasoning
Query wppsi_wm_pr Float Recommended Percentile - Working Memory
Query wppsi_bld_rawscre Integer Recommended Raw score Raw - Block Design 0 :: 40
Query wppsi_bld_scldscre Integer Recommended Scaled score SS - Block Design 0 :: 20
Query wppsi_inf_rawscre Integer Recommended Raw score Raw - Information 0 :: 34
Query wppsi_inf_scldscre Integer Recommended Scaled score SS - Information 0 :: 20
Query wppsi_mxr_rawscre Integer Recommended Raw score Raw - Matrix Reasoning 0 :: 29
Query wppsi_mxr_scldscre Integer Recommended Scaled score SS - Matrix Reasoning 0 :: 20
Query wppsi_vcb_rawscre Integer Recommended Raw score Raw - Vocabulary 0 :: 43
Query wppsi_vcb_scldscre Integer Recommended Scaled score SS - Vocabulary 0 :: 20
Query wppsi_pcn_rawscre Integer Recommended Raw score Raw - Picture Concepts 0 :: 28
Query wppsi_pcn_scldscre Integer Recommended Scaled score SS- Picture Concepts 0 :: 20
Query wppsi_sbs_rawscre Integer Recommended Raw score Raw - Symbol Search 0 :: 50 symbolsearchrawscore
Query wppsi_sbs_scldscre Integer Recommended Scaled score SS - Symbol Search 0 :: 20 symbolsearchscaledscore
Query wppsi_wrs_rawscre Integer Recommended Raw score Raw - Word Reasoning 0 :: 28
Query wppsi_wrs_scldscre Integer Recommended Scaled score SS - Word Reasoning 0 :: 20
Query wppsi_cdg_rawscre Integer Recommended Scaled score SS -Coding 0 :: 65 codingrawscore
Query wppsi_cdg_scldscre Integer Recommended Raw score Raw -Coding 0 :: 20 codingscaledscore
Query wppsi_cmp_rawscre Integer Recommended Raw score Raw - Comprehension 0 :: 38
Query wppsi_cmp_scldscre Integer Recommended Scaled score SS - Comprehension 0 :: 20
Query wppsi_bs_rawscre Integer Recommended Raw score Raw - Bug Search bugsearchrawscore
Query wppsi_bs_scldscre Integer Recommended Scaled score SS - Bug Search bugsearchscaledscore
Query wppsi_sml_rawscre Integer Recommended Raw score Raw - Similarities 0 :: 46
Query wppsi_sml_scldscre Integer Recommended Scaled score SS - Similarities 0 :: 20
Query wppsi_pm_rawscre Integer Recommended Raw score Raw - Picture Memory
Query wppsi_pm_scldscre Integer Recommended Scaled score SS - Picture Memory
Query wppsi_canc_rawscre Integer Recommended Raw score Raw - Cancellation cancellationrawscore
Query wppsi_canc_scldscre Integer Recommended Scaled score SS - Cancellation cancellationscaledscore
Query wppsi_zl_rawscre Integer Recommended Raw score Raw - Zoo Locations
Query wppsi_zl_scldscre Integer Recommended Scaled score SS - Zoo Locations
Query wppsi_ac_rawscre Integer Recommended Raw score Raw - Animal Coding
Query wppsi_ac_scldscre Integer Recommended Scaled score SS - Animal Coding
Query wppsi_cr_rawscre Integer Recommended Raw score Raw - Cancel Random
Query wppsi_cr_scldscre Integer Recommended Scaled score SS - Cancel Random
Query wppsi_cs_rawscre Integer Recommended Raw score Raw - Cancel Structured
Query wppsi_cs_scldscre Integer Recommended Scaled score SS - Cancel Structured
Query wppsi_viq_scldscre Integer Recommended Sum of scaled scores Sum - Verbal 2 :: 58
Query wppsi_piq_sumscld Integer Recommended Sum of scaled scores Sum - Performance 2 :: 58
Query wppsi_psd_sumscld Integer Recommended Sum of scaled scores Sum - Processing Speed 2 :: 38 processingspeedscaledsum
Query wppsi_fiq_sumscld Integer Recommended Full Scale IQ Sum of Scaled Scores 5 :: 150
Query wppsi_vcmp_sumscld Integer Recommended Sum of scaled scores Sum - Verbal Comprehension
Query wppsi_fr_sumscld Integer Recommended Sum of scaled scores Sum - Fluid Reasoning
Query wppsi_vm_sumscld Integer Recommended Sum of scaled scores Sum - Working Memory
Query wppsi_viq_compscre Integer Recommended Composite score Composite - Verbal IQ 46 :: 155
Query wppsi_piq_compscre Integer Recommended Composite score Composite - Performance IQ 45 :: 155
Query wppsi_psd_compscre Integer Recommended Composite score Composite - Processing Speed 40 :: 150 processingspeedcompositescore
Query wppsi_fiq_composite Integer Recommended Full Scale IQ Composite Score
Query wppsi_vcmp_composite Integer Recommended Composite score Composite - Verbal Comprehension
Query wppsi_fr_composite Integer Recommended Composite score Composite - Fluid Reasoning
Query wppsi_vm_composite Integer Recommended Composite score Composite - Working Memory
Query wppsi_rvcb_rawscre Integer Recommended Raw score - Receptive Vocabulary 999=N/A, Missing
Query wppsi_rvcb_scldscre Integer Recommended Scaled score SS - Receptive Vocabulary
Query wppsi_gl_scldscre Integer Recommended Sum of scaled scores Sum - General Language 999=N/A, Missing
Query wsf_oaraw Integer Recommended Object Assembly Raw Score 0::51;-999 -999 = Missing value
Query wsf_oass Integer Recommended Object Assembly Scaled Score 1::19;-999 -999 = Missing value
Query wppsi_picname_rawscre Integer Recommended Raw score - Picture Naming
Query wppsi_picname_scldscre Integer Recommended Scaled score SS - Picture Naming
Query timept Integer Recommended Time Point 888 = not applicable; 999 = missing wppsi_time
matrixreason_item14 Integer Recommended Item 14 0;1 0 = Fail; 1 = Correct
matrixreason_item15 Integer Recommended Item 15 0;1 0 = Fail; 1 = Correct
matrixreason_item16 Integer Recommended Item 16 0;1 0 = Fail; 1 = Correct
matrixreason_item17 Integer Recommended Item 17 0;1 0 = Fail; 1 = Correct
matrixreason_item18 Integer Recommended Item 18 0;1 0 = Fail; 1 = Correct
matrixreason_item19 Integer Recommended Item 19 0;1 0 = Fail; 1 = Correct
matrixreason_item2 Integer Recommended Item 2 0;1 0 = Fail; 1 = Correct
matrixreason_item20 Integer Recommended Item 20 0;1 0 = Fail; 1 = Correct
matrixreason_item21 Integer Recommended Item 21 0;1 0 = Fail; 1 = Correct
matrixreason_item22 Integer Recommended Item 22 0;1 0 = Fail; 1 = Correct
matrixreason_item23 Integer Recommended Item 23 0;1 0 = Fail; 1 = Correct
matrixreason_item24 Integer Recommended Item 24 0;1 0 = Fail; 1 = Correct
matrixreason_item25 Integer Recommended Item 25 0;1 0 = Fail; 1 = Correct
matrixreason_item26 Integer Recommended Item 26 0;1 0 = Fail; 1 = Correct
matrixreason_item3 Integer Recommended Item 3 0;1 0 = Fail; 1 = Correct
matrixreason_item4 Integer Recommended Item 4 0;1 0 = Fail; 1 = Correct
matrixreason_item5 Integer Recommended Item 5 0;1 0 = Fail; 1 = Correct
matrixreason_item6 Integer Recommended Item 6 0;1 0 = Fail; 1 = Correct
matrixreason_item7 Integer Recommended Item 7 0;1 0 = Fail; 1 = Correct
matrixreason_item8 Integer Recommended Item 8 0;1 0 = Fail; 1 = Correct
discontinue Integer Recommended Rules Triggered, Discontinue
matrixreason_item9 Integer Recommended Item 9 0;1 0 = Fail; 1 = Correct
reverse Integer Recommended Rules Triggered, Reverse
wppsi_mxr_p Integer Recommended Subtest Type Prompt (P), Total
pea_wppsi_item_a_rs Integer Recommended WPPSI-IV Ages 4-7 Matrix Reasoning Sample Item A
0;1
0 = Incorrect; 1 = Correct
pea_wppsi_item_b_rs Integer Recommended WPPSI-IV Ages 4-7 Matrix Reasoning Sample Item B
0;1
0 = Incorrect; 1 = Correct
pea_wppsi_item_c_rs Integer Recommended WPPSI-IV Ages 4-7 Matrix Reasoning Sample Item C
0;1
0 = Incorrect; 1 = Correct
matrix_completion Float Recommended Matrix Reasoning Completion time (seconds)
matrixreason_item1 Integer Recommended Item 1 0;1 0 = Fail; 1 = Correct
matrixreason_item10 Integer Recommended Item 10 0;1 0 = Fail; 1 = Correct
matrixreason_item11 Integer Recommended Item 11 0;1 0 = Fail; 1 = Correct
matrixreason_item12 Integer Recommended Item 12 0;1 0 = Fail; 1 = Correct
matrixreason_item13 Integer Recommended Item 13 0;1 0 = Fail; 1 = Correct
subtesttypedk Float Recommended Subtest Type Don't Know (DK),Total wppsi_mxr_dk
subtesttypenr Integer Recommended Subtest Type No Response (NR),Total wppsi_mxr_nr
comqother String 255 Recommended Respondent - Other (text)
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.