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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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CELF Preschool-2

172 Shared Subjects

Clinical Evaluation of Language Fundamentals - Preschool, Second Edition (CELF Preschool-2) (2004) as defined by University of Illinois at Chicago
Clinical Assessments
Speech-Language
05/26/2010
celf_p201
05/26/2010
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* Unique_ID
src_subject_id String 20 Required Subject ID how it's defined in lab/project Subject_ID, plot_id
interview_date Date Required Date on which the interview/genetic test/sampling/imaging/biospecimen was completed. MM/DD/YYYY Required field CELFP2_DOE, plot_session1date
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. CELFP2_CA, plot_age_totalmonths
Query celfp2_measure String 20 Recommended Measure Used CELF-P2
Query celfp2_year String 20 Recommended CELF-P2: year from published/most recent copywrite 2004
Query celfp2_sents_raw Integer Required Sentence Structure. Raw Score 0 :: 22; 999 999 = Not available celfp2_sentstrct_raw
Query celfp2_sents_scld Integer Recommended CELF-P2 Sentence Structure Scaled Score 1 :: 19 celfp2_sentstrct_scaled
Query celfp2_sents_percent_rk String 20 Recommended Sentence Structure. Percentile Rank celfp2_sentstrct_perc
Query celfp2_sents_ae String 10 Recommended CELF-P2 Sentence Structure Age Equivalent (in months) celfp2_sentstrct_ae
Query celfp2_ws_raw Integer Required Word Structure. Raw Score 0 :: 24; 999 999 = Not available celf_ws_raw, celfp2_wordstrct_raw
Query celfp2_ws_scld Integer Recommended CELF-P2 Word Structure Scaled Score 1 :: 19 celf_ws_scld_scr, celfp2_wordstrct_scaled
Query celfp2_ws_percent_rk String 20 Recommended Word Structure. Percentile Rank celfp2_wordstrct_perc
Query celfp2_ws_ae String 10 Recommended CELF-P2 Word Structure Age Equivalent (in months) celf_ws_ae, celfp2_wordstrct_ae
Query celfp2_ev_raw Integer Required CELF-P2 Expressive Vocabulary Raw Score 0 :: 40; 999 999 = Not available celfp2_expvocab_raw
Query celfp2_ev_scld Integer Recommended CELF-P2 Expressive Vocabulary Scaled Score 1 :: 19 celfp2_expvocab_scaled
Query celfp2_ev_percent_rk String 20 Recommended CELF-P2 Expressive Vocabulary Scaled Score Percentile Rank (<0.1 to >99.9) celfp2_expvocab_perc
Query celfp2_ev_ae String 10 Recommended CELF-P2 Expressive Vocabulary Age Equivalent (in months) celfp2_expvocab_ae
Query celfp2_cfd_raw Integer Required CELF-P2 Concepts & Following Directions Raw Score 0 :: 22; 999 999 = Not available
Query celfp2_cfd_scld Integer Recommended CELF-P2 Concepts & Following Directions Scaled Score 1 :: 19
Query celfp2_cfd_percent_rk String 20 Recommended CELF-P2 Concepts & Following Directions Scaled Score Percentile Rank (<0.1 to >99.9)
Query celfp2_cfd_ae String 10 Recommended CELF-P2 Concepts & Following Directions Age Equivalent (in months)
Query celfp2_rs_raw Integer Required CELF-P2 Recalling Sentences Raw Score 0 :: 39; 999 999 = Not available
Query celfp2_rs_scld Integer Recommended CELF-P2 Recalling Sentences Scaled Score 1 :: 19
Query celfp2_rs_percent_rk String 20 Recommended CELF-P2 Recalling Sentences Scaled Score Percentile Rank (<0.1 to >99.9)
Query celfp2_rs_ae String 10 Recommended CELF-P2 Recalling Sentences Age Equivalent (in months)
Query celfp2_bc_raw Integer Required Basic Concepts. Raw Score 0 :: 18; 999 999 = Not available
Query celfp2_bc_scld Integer Recommended CELF-P2 Basic Concepts Scaled Score 1 :: 19
Query celfp2_bc_percent_rk String 20 Recommended Basic Concepts. Percentile Rank
Query celfp2_bc_ae String 10 Recommended CELF-P2 Basic Concepts Age Equivalent (in months)
Query celfp2_wc_r_raw Integer Required CELF-P2 Word Classes Receptive Raw Score 0 :: 20; 999 999 = Not available
Query celfp2_wc_r_scld Integer Recommended CELF-P2 Word Classes Receptive Scaled Score 1 :: 19
Query celfp2_wc_r_percent_rk String 20 Recommended CELF-P2 Word Classes Receptive Scaled Score Percentile Rank (<0.1 to >99.9)
Query celfp2_wc_r_ae String 10 Recommended CELF-P2 Word Classes Receptive Age Equivalent (in months)
Query celfp2_wc_e_raw Integer Required CELF-P2 Word Classes Expressive Raw Score 0 :: 20; 999 999 = Not available
Query celfp2_wc_e_scld Integer Recommended CELF-P2 Word Classes Expressive Scaled Score 1 :: 19
Query celfp2_wc_e_percent_rk String 20 Recommended CELF-P2 Word Classes Expressive Scaled Score Percentile Rank (<0.1 to >99.9)
Query celfp2_wc_e_ae String 10 Recommended CELF-P2 Word Classes Expressive Age Equivalent (in months)
Query celfp2_wc_t_raw Integer Required CELF-P2 Word Classes Total Raw Score (Ages 4-6) 0 :: 40; 999 999 = Not available
Query celfp2_wc_rplswc_e_scld_sum Integer Recommended CELF-P2 Word Classes Sum of WC-R and WC-E Scaled Scores 2 :: 38
Query celfp2_wc_t_scld Integer Recommended CELF-P2 Word Classes Total Scaled Score 1 :: 19
Query celfp2_wc_t_percent_rk String 20 Recommended CELF-P2 Word Classes Total Scaled Score Percentile Rank (<0.1 to >99.9)
Query celfp2_wc_t_ae String 10 Recommended CELF-P2 Word Classes Total Age Equivalent (in months)
Query celfp2_cl_sum Integer Recommended CELF-P2 Core Language Sum of Scaled Scores 3 :: 57 celf_cl_Sum_scld_scr, celfp2_corelang_sum_scaled
Query celfp2_cl_ss Integer Recommended CELF-P2 Core Language Standard Score 45 :: 155 celf_cl_ss, celfp2_corelang_sum_stndrd
Query celfp2_cl_percent_rk String 20 Recommended CELF-P2 Core Language Percentile Rank (<0.1 to >99.9) celfp2_corelang_sum_perc
Query celfp2_rli_sum Integer Recommended CELF-P2 Receptive Language Index Sum of Scaled Scores 3 :: 57
Query celfp2_rli_ss Integer Recommended CELF-P2 Receptive Language Index Standard Score 45 :: 155
Query celfp2_rli_percent_rk String 20 Recommended CELF-P2 Receptive Language Index Percentile Rank (<0.1 to >99.9)
Query celfp2_eli_sum Integer Recommended CELF-P2 Expressive Language Index Sum of Scaled Scores 3 :: 57
Query celfp2_eli_ss Integer Recommended CELF-P2 Expressive Language Index Standard Score 45 :: 155
Query celfp2_eli_percent_rk String 20 Recommended CELF-P2 Expressive Language Index Percentile Rank (<0.1 to >99.9)
Query celfp2_lci_sum Integer Recommended CELF-P2 Language Content Index Sum of Scaled Scores 3 :: 57
Query celfp2_lci_ss Integer Recommended CELF-P2 Language Content Index Standard Score 45 :: 155
Query celfp2_lci_percent_rk String 20 Recommended CELF-P2 Language Content Index Percentile Rank (<0.1 to >99.9)
Query celfp2_lsi_sum Integer Recommended CELF-P2 Language Structure Index Sum of Scaled Scores 3 :: 57
Query celfp2_lsi_ss Integer Recommended CELF-P2 Language Structure Index Standard Score 45 :: 155
Query celfp2_lsi_percent_rk String 20 Recommended CELF-P2 Language Structure Index Percentile Rank (<0.1 to >99.9)
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.