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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 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.

    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.

  • 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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Description
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Data Structures with shared data
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Hostile Intent Attribution Measure

212 Shared Subjects

N/A
Clinical Assessments
Personality
01/18/2018
iam01
01/18/2018
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
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
Query has1a Integer Recommended Radio: Imagine that you brought your new radio to school today. You saved up your allowance to buy the radio and you want to show it to the other kids at school. You let another kid play with it for a few minutes while you get a drink of water. When you get back you realize that the kid has broken your new radio. Why did the kid break your radio? 1 :: 4 1 = The radio wasn't made well, 2 = It was an accident, 3 = The kid was mad at me, 4 = The kid was jealous of me.
Query has1b Integer Recommended Radio: In this story, do you think the kid was 1 :: 2 1 = Trying to be mean? 2 = Not trying to be mean?
Query has1c Integer Recommended Radio: How upset or mad would you be if the things in this story really happened to you? 1 :: 3 1 = Not upset or mad at all, 2 = A little upset or mad, 3 = Very upset or mad
Query has1d Integer Recommended Radio: How upset would you be if the things in this story really happened to you? 1 :: 3 1 = Not upset at all; 2 = A little upset; 3 = Very upset
Query has1e Integer Recommended Radio: How mad would you be if the things in this story really happened to you? 1 :: 3 1 = Not mad at all; 2 = A little mad; 3 = Very mad
Query has2a Integer Recommended Lunch hour: Imagine that you are looking for your friend over the lunch hour. You can't wait to find your friend because you have an important secret to share. By the time you find your friend, your friend is already talking with someone else - a kid that you don't like very much. Why did your friend talk to someone else instead of you? 1 :: 4 1 = My friend was mad at me, 2 = My friend didn't know that I wanted to talk with them, 3 = My friend wanted to get back at me for something, 4 = My friend didn't see me in the lunch room.
Query has2b Integer Recommended Lunch hour: In this story, do you think the kid was 1 :: 2 1 = Trying to be mean? 2 = Not trying to be mean?
Query has2c Integer Recommended Lunch hour: How upset or mad would you be if the things in this story really happened to you? 1 :: 3 1 = Not upset or mad at all, 2 = A little upset or mad, 3 = Very upset or mad
Query has2d Integer Recommended Lunch hour: How upset would you be if the things in this story really happened to you? 1 :: 3 1 = Not upset at all; 2 = A little upset; 3 = Very upset
Query has2e Integer Recommended Lunch hour: How mad would you be if the things in this story really happened to you? 1 :: 3 1 = Not mad at all; 2 = A little mad; 3 = Very mad
Query has3a Integer Recommended Cut in line: At school one day, you are lining up with your class, like for lunch. Just as you are getting in line, a kid in your class says, "I want this spot." Then the kid cuts in front of you. Why did the kid cut in front of you? 1 :: 4 1 = The kid had to rush to the bathroom, 2 = The kid was trying to make me mad, 3 = The kid always cuts in front of me, 4 = The kid didn't see that I was already in line.
Query has3b Integer Recommended Cut in line: In this story, do you think the kid was 1 :: 2 1 = Trying to be mean? 2 = Not trying to be mean?
Query has3c Integer Recommended Cut in line: How upset or mad would you be if the things in this story really happened to you? 1 :: 3 1 = Not upset or mad at all, 2 = A little upset or mad, 3 = Very upset or mad
Query has3d Integer Recommended Cut in line: How upset would you be if the things in this story really happened to you? 1 :: 3 1 = Not upset at all; 2 = A little upset; 3 = Very upset
Query has3e Integer Recommended Cut in line: How mad would you be if the things in this story really happened to you? 1 :: 3 1 = Not mad at all; 2 = A little mad; 3 = Very mad
Query has4a Integer Recommended Milk: Imagine that you are sitting at the lunch table at school, eating lunch. You look up and see another kid coming over to your table with a carton of milk. You turn around to eat your lunch, and the next thing that happens is that the kid spills milk all over your back. The milk gets your shirt all wet. Why did the kid spill milk all over your back? 1 :: 4 1 = The kid slipped on something, 2 = The kid just does stupid things like that to me, 3 = The kid wanted to make fun of me, 4 = The kid wasn't looking where she or he was going.
Query has4b Integer Recommended Milk: In this story, do you think the kid was 1 :: 2 1 = Trying to be mean? 2 = Not trying to be mean?
Query has4c Integer Recommended Milk: How upset or mad would you be if the things in this story really happened to you? 1 :: 3 1 = Not upset or mad at all, 2 = A little upset or mad, 3 = Very upset or mad
Query has4d Integer Recommended Milk: How upset would you be if the things in this story really happened to you? 1 :: 3 1 = Not upset at all; 2 = A little upset; 3 = Very upset
Query has4e Integer Recommended Milk: How mad would you be if the things in this story really happened to you? 1 :: 3 1 = Not mad at all; 2 = A little mad; 3 = Very mad
Query has5a Integer Recommended Hallway: You are standing in the hallway one morning before school. As you are standing there, two kids from your class walk by. Although they are whispering, you overhear the kids say something mean about you to each other. As they walk by, the two kids look at you and then laugh as they walk down the hall. Why did the two kids laugh when they walked by you? 1 :: 4 1 = The kids were making fun of me, 2 = The kids were laughing at a joke that one of them told, 3 = The kids were just having fun, 4 = The kids were trying to make me mad.
Query has5b Integer Recommended Hallway: In this story, do you think the kid was 1 :: 2 1 = Trying to be mean? 2 = Not trying to be mean?
Query has5c Integer Recommended Hallway: How upset or mad would you be if the things in this story really happened to you? 1 :: 3 1 = Not upset or mad at all, 2 = A little upset or mad, 3 = Very upset or mad
Query has5d Integer Recommended Hallway: How upset would you be if the things in this story really happened to you? 1 :: 3 1 = Not upset at all; 2 = A little upset; 3 = Very upset
Query has5e Integer Recommended Hallway: How mad would you be if the things in this story really happened to you? 1 :: 3 1 = Not mad at all; 2 = A little mad; 3 = Very mad
Query has6a Integer Recommended Shoes: Imagine that you are walking to school and you're wearing your new tennis shoes. You really like your new shoes and this is the first day you have worn them. Suddenly, you are bumped from behind by another kid. You stumble and fall into a mud puddle and your new shoes get muddy. Why did the kid bump you from behind? 1 :: 4 1 = The kid was being mean, 2 = The kid was fooling around and pushed too hard by accident, 3 = The kid was running down the street and didn't see me, 4 = The kid was trying to push me down.
Query has6b Integer Recommended Shoes: In this story, do you think the kid was 1 :: 2 1 = Trying to be mean? 2 = Not trying to be mean?
Query has6c Integer Recommended Shoes: How upset or mad would you be if the things in this story really happened to you? 1 :: 3 1 = Not upset or mad at all, 2 = A little upset or mad, 3 = Very upset or mad
Query has6d Integer Recommended Shoes: How upset would you be if the things in this story really happened to you? 1 :: 3 1 = Not upset at all; 2 = A little upset; 3 = Very upset
Query has6e Integer Recommended Shoes: How mad would you be if the things in this story really happened to you? 1 :: 3 1 = Not mad at all; 2 = A little mad; 3 = Very mad
Query has7a Integer Recommended Birthday party: Imagine that you are in the bathroom one day after recess. While you are in there, two other kids from your class come in and start talking to each other. You hear one of the kids invite the other one to a birthday party. The kid says that there are going to be a lot of people at the party. You have not been invited to this party. Why hasn't the kid invited you to his party? 1 :: 4 1 = The kid doesn't want me to come to her/his party, 2 = The kid hasn't had a chance to invite me yet, 3 = The kid is trying to get back at me for something, 4 = The kid was planning to invite me later.
Query has7b Integer Recommended Birthday party: In this story, do you think the kid was 1 :: 2 1 = Trying to be mean? 2 = Not trying to be mean?
Query has7c Integer Recommended Birthday party: How upset or mad would you be if the things in this story really happened to you? 1 :: 3 1 = Not upset or mad at all, 2 = A little upset or mad, 3 = Very upset or mad
Query has7d Integer Recommended Birthday party: How upset would you be if the things in this story really happened to you? 1 :: 3 1 = Not upset at all; 2 = A little upset; 3 = Very upset
Query has7e Integer Recommended Birthday party: How mad would you be if the things in this story really happened to you? 1 :: 3 1 = Not mad at all; 2 = A little mad; 3 = Very mad
Query has8a Integer Recommended Art project: Imagine that you have just finished an art project for school. You've worked on it a long time and you're really proud of it. Another kid comes over to look at your project. The kid is holding a jar of paint. You turn away for a minute and when you look back the kid has spilled paint on your project. You worked on the project for a long time and now it's ruined. Why did the kid spill paint on your project? 1 :: 4 1 = The kid is mean, 2 = The kid bumped into the paint by accident, 3 = The kid is kind of clumsy, 4 = The kid wanted to ruin my project.
Query has8b Integer Recommended Art project: In this story, do you think the kid was 1 :: 2 1 = Trying to be mean? 2 = Not trying to be mean?
Query has8c Integer Recommended Art project: How upset or mad would you be if the things in this story really happened to you? 1 :: 3 1 = Not upset or mad at all, 2 = A little upset or mad, 3 = Very upset or mad
Query has8d Integer Recommended Art project: How upset would you be if the things in this story really happened to you? 1 :: 3 1 = Not upset at all; 2 = A little upset; 3 = Very upset
Query has8e Integer Recommended Art project: How mad would you be if the things in this story really happened to you? 1 :: 3 1 = Not mad at all; 2 = A little mad; 3 = Very mad
Query has9a Integer Recommended Excluded: You are at lunch one day and looking for a place to sit. You see kids you know at a table across the room. The kids are laughing and talking to each other and they look like they are having a good time. You go over to their table, sit down, and say hi to everyone. The kids look right at you, roll their eyes, and don't say anything to you. After a few seconds, the kids start talking again to each other, but no one talks to you at all. Why are the kids not talking to you? 1 :: 4 1 = They are mad with me, 2 = They didn't hear me say hi, 3 = They are always mean to me, 4 = They were talking about their group project.
Query has9b Integer Recommended Excluded: In this story, do you think the kid was 1 :: 2 1 = Trying to be mean? 2 = Not trying to be mean?
Query has9c Integer Recommended Excluded: How upset or mad would you be if the things in this story really happened to you? 1 :: 3 1 = Not upset or mad at all, 2 = A little upset or mad, 3 = Very upset or mad
Query has9d Integer Recommended Excluded: How upset would you be if the things in this story really happened to you? 1 :: 3 1 = Not upset at all; 2 = A little upset; 3 = Very upset
Query has9e Integer Recommended Excluded: How mad would you be if the things in this story really happened to you? 1 :: 3 1 = Not mad at all; 2 = A little mad; 3 = Very mad
Query has10a Integer Recommended Race: Imagine that you are in gym class. You and some other kids are having a race. Another kid is standing on the side, bouncing a basketball. The next thing you realize is that the kid has bounced the ball and it rolls under your feet, making you fall. You skin your knee and someone else wins the race. Why did the kid bounce the ball under your feet? 1 :: 4 1 = The kid wanted to get back at me for something, 2 = The kid didn't see me coming, 3 = The ball accidentally got away from the kid, 4 = The kid wanted me to lose the race.
Query has10b Integer Recommended Race: In this story, do you think the kid was 1 :: 2 1 = Trying to be mean? 2 = Not trying to be mean?
Query has10c Integer Recommended Race: How upset or mad would you be if the things in this story really happened to you? 1 :: 3 1 = Not upset or mad at all, 2 = A little upset or mad, 3 = Very upset or mad
Query has10d Integer Recommended Race: How upset would you be if the things in this story really happened to you? 1 :: 3 1 = Not upset at all; 2 = A little upset; 3 = Very upset
Query has10e Integer Recommended Race: How mad would you be if the things in this story really happened to you? 1 :: 3 1 = Not mad at all; 2 = A little mad; 3 = Very mad
Query has11a Integer Recommended Taking a walk: Imagine that you are taking a walk in your neighborhood one day. After you walk a block or two, you see two kids that you know from school. You walk over to the kids and say "hi". The two kids act as if you are not there--- they don't say anything to you. Then they say something to each other that you can't hear and they walk the other way. Why didn't the two kids say hello to you? 1 :: 4 1 = They didn't see me standing there, 2 = They didn't hear me say hi first, 3 = They were mad at me about something, 4 = They don't like me.
Query has11b Integer Recommended Taking a walk: In this story, do you think the kid was 1 :: 2 1 = Trying to be mean? 2 = Not trying to be mean?
Query has11c Integer Recommended Taking a walk: How upset or mad would you be if the things in this story really happened to you? 1 :: 3 1 = Not upset or mad at all, 2 = A little upset or mad, 3 = Very upset or mad
Query has11d Integer Recommended Taking a walk: How upset would you be if the things in this story really happened to you? 1 :: 3 1 = Not upset at all; 2 = A little upset; 3 = Very upset
Query has11e Integer Recommended Taking a walk: How mad would you be if the things in this story really happened to you? 1 :: 3 1 = Not mad at all; 2 = A little mad; 3 = Very mad
Query has12a Integer Recommended Playground: Imagine that you are looking for your friend on the playground. You can't wait to find your friend because you have an important secret to share. By the time you find your friend, your friend is already playing with someone else - a kid that you don't like very much. Why did your friend play with someone else instead of you? 1 :: 4 1 = My friend was mad at me, 2 = My friend didn't know that I wanted to play with them, 3 = My friend wanted to get back at me for something, 4 = My friend didn't see me on the playground.
Query has12b Integer Recommended Playground: In this story, do you think the kid was 1 :: 2 1 = Trying to be mean? 2 = Not trying to be mean?
Query has12d Integer Recommended Playground: How upset would you be if the things in this story really happened to you? 1 :: 3 1 = Not upset at all; 2 = A little upset; 3 = Very upset
Query has12e Integer Recommended Playground: How mad would you be if the things in this story really happened to you? 1 :: 3 1 = Not mad at all; 2 = A little mad; 3 = Very mad
comments_misc String 4,000 Recommended Miscellaneous comments on study, interview, methodology relevant to this form data
Query has_score1 Integer Recommended Radio: Hostile Attribution Bias Score 1
Query has_score2 Integer Recommended Lunch hour: Hostile Attribution Bias Score 2
Query has_score3 Integer Recommended Cut in line: Hostile Attribution Bias Score 3
Query has_score4 Integer Recommended Milk: Hostile Attribution Bias Score 4
Query has_score5 Integer Recommended Hallway: Hostile Attribution Bias Score 5
Query has_score6 Integer Recommended Shoes: Hostile Attribution Bias Score 6
Query has_score7 Integer Recommended Birthday party: Hostile Attribution Bias Score 7
Query has_score8 Integer Recommended Art project: Hostile Attribution Bias Score 8
Query has_score9 Integer Recommended Excluded: Hostile Attribution Bias Score 9
Query has_score10 Integer Recommended Race: Hostile Attribution Bias Score 10
Query has_score11 Integer Recommended Taking a walk: Hostile Attribution Bias Score 11
Query has_score12 Integer Recommended Playground: Hostile Attribution Bias Score 12
Query has_score_total Integer Recommended Hostile Attribution Bias Total Score
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

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