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IPEDS Peer Analysis System Advanced Module. The place to go for IPEDS data: http://nces.ed.gov/ipeds. Session Agenda. Data availability and issues Important data concepts Review of Peer Analysis System Basics Advanced features Research Questions with PAS

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Ipeds peer analysis system advanced module

IPEDSPeer Analysis SystemAdvanced Module

The place to go for

IPEDS data:

http://nces.ed.gov/ipeds


Session agenda
Session Agenda

  • Data availability and issues

  • Important data concepts

  • Review of Peer Analysis System

    • Basics

    • Advanced features

  • Research Questions with PAS

    • Average freshman tuition discount

    • Expenditure comparison

    • Schools offering a specific degree


Data available in the peer analysis system
Data Available in thePeer Analysis System

  • 1980, 1984, 1985 HEGIS data

  • 1986 – 2004 IPEDS data

  • Selected HEGIS data not in the PAS are available at through the International Archive of Education Data housed at the University of Michigan.


Availability caveats
Availability Caveats

  • Not all data are available for all years

  • New surveys have been added over time

  • Some data fields have been discontinued

  • New data fields have been added

  • Definitions may change



Data issues
Data Issues

  • Changes in finance reporting standards began in 1997 and have been phased in over a period of time. Now, most privates use FASB and most publics use GASB. However, there is still great variability in Finance data that makes inter-institutional comparisons problematic.


More data issues
More Data Issues

  • Some data required in alternate years, but some schools submit for all years:

    • Enrollment by age: odd years

    • Residence of first-year students: even years

    • Fall staff: odd years

      Be very careful working with data from the years when submission is not required.


And more data issues
And More Data Issues…

  • Until submitting new variables is mandatory, not all schools submit data for them.

  • Continuing education is defined differently by different schools.

  • NCES began allowing schools to enter their own FTE values for 2002-03 data year


Important data concepts
Important Data Concepts

  • Collection year vs. data year

  • Imputation and perturbation

  • Release sequence of IPEDS data

  • Structure of IPEDS data files

  • Frequently used/derived variables


Ipeds peer analysis system advanced module

1. Collection Year vs. Data Year

  • Collection year:academic year in which the data are collected by NCES during the fall, winter, and spring collection cycle

  • Data year:academic year the data represent, which may be prior to the collection year



Master variables list selection
Master Variables List Selection

The surveys and the years for which data are available are displayed on the Master Variables List Selection screen.


2 disclosure protection
2. Disclosure Protection

  • NCES is required by law to protect against disclosure of individually identifiable information collected in the IPEDS surveys

  • Impacts four IPEDS data files:

    • Graduation Rates

    • Student Financial Aid

    • Salaries

    • Fall Staff


Perturbation
Perturbation

  • Random alteration of data in cells with small number of observations

  • Protects the confidentiality of individually identifiable data

  • Occurs during migration of data from data collection system to the PAS

  • It’s unpopular—but the alternative is data suppression


Data sharing
Data Sharing

  • Data that an institution puts into IPEDS

    • Belong to the institution

    • May be shared

    • BUT, may be subject to FERPA

  • Data IN the IPEDS data collection system

    • Technically belong to NCES

    • Are subject to NCES confidentiality requirements

    • May NOT be shared

  • Data in the IPEDS Peer Analysis System

    • Have been perturbed

    • Protect individually identifiable information

    • May be shared


Ipeds peer analysis system advanced module

This pop-up window precedes any data access. You must agree to the terms in order to proceed with your analysis.


Imputation
Imputation to the terms in order to proceed with your analysis.

  • IPEDS data are imputed for total nonresponse and item nonresponse

    • Various methods used such as prior year adjusted values, nearest neighbor, group means

  • Imputation allows files to be used for national totals

  • Imputed values appear on final data files

  • Web data input has dramatically reduced the need to impute data values


3 data release stages
3. to the terms in order to proceed with your analysis. Data Release Stages

  • Pre-release: login at collection level

    • Data are reviewed and perturbed

    • Locked institutions are migrated to PAS

    • Data available for peer comparisons only

  • Early release: login at institution level

    • All institutions are migrated to PAS

    • Data available for peer comparisons only

  • Final release: login at guest level

    • Data are imputed and fully adjudicated

    • No restrictions on data use


4 structure of ipeds data files
4. to the terms in order to proceed with your analysis. Structure of IPEDS Data Files

  • Single-record files contain one line of data for each institution—for example, data in the Institutional Characteristics survey

  • Multiple-record files contain several lines of data for each institution—for example, data by race/ethnicity and gender inthe Enrollment survey


Single record file
Single-Record File to the terms in order to proceed with your analysis.


Multiple record file
Multiple-Record File to the terms in order to proceed with your analysis.


Qualifying variables
Qualifying Variables to the terms in order to proceed with your analysis.

  • When choosing variables from multiple-record files, the user must first specify the qualifying variables

  • The user’s choice tells PAS which records to select for the analysis


Ipeds peer analysis system advanced module

For example, in order to select Hispanic students, you must specify which Hispanic students. All Hispanic students?

Full-time Hispanic students? Undergraduate Hispanic students?

Level of student is the qualifying variable that lets you to choose. Here, choose

Full-time students total and Part-time students total.




5 frequently used derived variables
5. possible combination: Frequently Used/Derived Variables

  • Permanent “calculated variables

    • frequently used “institution” variables, e.g.,total enrollment, tuition and fees

    • data feedback report variables

    • College Affordability Index variables

  • Developed by NCES from existing IPEDS survey variables

  • Available beginning in 2002


The peer analysis system is the fastest way to capture ipeds data for your analyses
The Peer Analysis System possible combination:is the fastest way to captureIPEDS data for your analyses!

Review of strategies


Analysis strategy
Analysis Strategy possible combination:

  • Select a group of colleges and universities

  • Identify variables for years of interest and retrieve those data for the group of schools

  • Generate reports useful for policy analysis, peer comparisons, assessment, administrative decision-making, etc.


3 steps to peer analysis
3 Steps to Peer Analysis: possible combination:

1. Identify a LinchPin institution

  • the institution you want to compare with others

    2. Construct a comparison group

    3. Prepare your analysis

  • generate reports, files, statistics, graphs


Comparison group
Comparison Group possible combination:

  • Three methods of construction

    • Select by name or UnitID

    • Select by variable (shared characteristics)

    • Auto peer group

  • Peer groups can be saved to your hard drive for later use as files with a ‘uid’ extension


Types of analyses reports stats
Types of Analyses = Reports & Stats possible combination:

  • Ranking report

    • One variable, with values sorted high to low

  • Institutions Data report

    • Multiple variables, perhaps from multiple files

  • Statistical Summary report

    • Basic descriptive statistics, with optional graphs

  • Report Templates

    • Prepackaged formats

  • Forms Facsimile

    • Survey data, presented in survey grid format


Master variables list
Master Variables List possible combination:

  • Stores all variables used in a session

  • Accessible through Main Menu  Session Summary

  • Lists can be saved to your hard drive with an .mvl extension


Calculated variables
Calculated Variables possible combination:

  • Three types:

    • Summation

    • Difference

    • Ratio

  • Can be built from IPEDS variables

  • Can be built from calculated variables

  • Can be saved to your hard drive as part of a Master Variables List


Support during your session
Support During Your Session possible combination:

  • Session Summary

    • via Main Menu

  • On-line User Manual

    • can be printed

  • Help buttons

    • available on most pages

  • Info buttons

    • define variable characteristics


Log on to the peer analysis system

Log On to the possible combination:Peer Analysis System

http://nces.ed.gov/ipeds


Ipeds peer analysis system advanced module

Select the possible combination:

Peer Analysis System


Ipeds peer analysis system advanced module

Login at the Institution level, which includes early release data with missing values not yet imputed.


Ipeds peer analysis system advanced module

You can use your institution’s UnitID or choose another.

Find other UnitIDs using IPEDS Cool.


Ipeds peer analysis system advanced module

You can use your own institution as LinchPin, data with missing values not yet imputed.

or select another school that you want as the focus of your analysis


Ipeds peer analysis system advanced module

Session Summary identifies the LinchPin institution with no institutions in the comparison group and no variables in the Master Variables List.

Click on Main Menu whenever you want to see a Session Summary or to access your Master Variables List.


Research question
Research Question institutions in the comparison group and no variables in the Master Variables List.

  • What is the average first-year tuition discount rate for private schools in California?

    Most private institutions allocate some of their own resources to fund scholarships to attract new students. In the aggregate, these scholarships reduce the institution’s average tuition.


Calculation strategy
Calculation Strategy institutions in the comparison group and no variables in the Master Variables List.

Michael Duggan and Rebecca Matthews developed the following strategy: Freshman discount rate is the ratio of institutional grant aid to gross tuition revenue for the full-time first-time cohort.


Variables required
Variables Required institutions in the comparison group and no variables in the Master Variables List.

  • For gross tuition revenue generated by new freshmen:

    • Tuition rate

    • Number of freshmen in cohort

  • For total institutional grant aid awarded to new freshmen:

    • Number of freshmen awarded institutional aid

    • Average amount of institutional aid awarded


Ipeds survey sources
IPEDS Survey Sources institutions in the comparison group and no variables in the Master Variables List.

Constraint:

The most recent financial aid data is 2003-04, so all variables should be selected for this year.


Define comparison group
Define Comparison Group institutions in the comparison group and no variables in the Master Variables List.

  • From Institutional Characteristics, 2003, add

    • State abbreviation

    • Sector of institution

  • To apply this exercise to public institutions, you would have to know the percentages of in-state and out-of-state students for each school.


Build master variables list
Build Master Variables List institutions in the comparison group and no variables in the Master Variables List.

  • From Institutional Characteristics and Student Charges, 2003, add:

    • Published in-state tuition and fees 2003-04 from Price of attendance of full-time, first-time undergraduate students (charges for full academic yr)


Ipeds peer analysis system advanced module

  • From Enrollments, 2003, institutions in the comparison group and no variables in the Master Variables List.from Total entering class: Fall 2003,add

    • Full-time first-time degree/certificate-seeking undergraduate (current years GRS cohort)


Ipeds peer analysis system advanced module

  • From Student Financial Aid, 2004, institutions in the comparison group and no variables in the Master Variables List.from Student counts and financial aid, academic year 2003-04,from Financial Aid: Full-Time First-Time Degree/Certificate-Seeking Undergraduates, add

    • Number receiving institutional grant aid

    • Average amount of institutional grant aid received


Run institutions data report
Run Institutions Data Report institutions in the comparison group and no variables in the Master Variables List.

  • Select Reports and Stats, Institutions Data Report

  • From your Master Variables List, select all four variables

  • Specify long variable names

  • Download your results in csv format and save as an Excel file


Ipeds peer analysis system advanced module

…and it looks like this institutions in the comparison group and no variables in the Master Variables List.


Do calculations in excel
Do Calculations in Excel institutions in the comparison group and no variables in the Master Variables List.

  • Total Tuition and Fees(tuition x number in freshman cohort)

  • Total Institutional Grant Aid(number receiving grant aid x average award)

  • Average Freshman Discount Rate(Institutional Grant Aid / Total Tuition & Fees)


Create an attractive report
Create an Attractive Report institutions in the comparison group and no variables in the Master Variables List.

  • Add a report title

  • Adjust column widths and column titles

  • Sort from high to low on average freshman discount rate


Ipeds peer analysis system advanced module

-Total Tuition Revenue institutions in the comparison group and no variables in the Master Variables List.

-Total Grant Aid

- Freshman Discount Rate

Add a title, modify the headings, and format the numbers. It’s a report!


Research questions
Research Questions institutions in the comparison group and no variables in the Master Variables List.

  • What percent of “core” expenditures (as defined by NCES) is represented by instruction?

  • Have these percentages changed between 2002 and 2004?

    Answer these questions for four-year public doctoral/research institutions in Georgia and Alabama.


Define comparison group1
Define Comparison Group institutions in the comparison group and no variables in the Master Variables List.

  • Add by Variable

  • From Institutional Characteristics, 2004, add

    • State abbreviation

    • Sector of institution

    • Carnegie Classification code


Query form
Query Form institutions in the comparison group and no variables in the Master Variables List.


Comparison group1
Comparison Group institutions in the comparison group and no variables in the Master Variables List.


Add to master variables list
Add to Master Variables List institutions in the comparison group and no variables in the Master Variables List.

  • From Finance, 2004,from Frequently used financial indicators for all institutions: Fiscal year 2004, add

    • Core expenses, total dollar

      from Public institutions - GASB 34/35: Fiscal year 2004, add

    • Instruction - current year total


Ipeds peer analysis system advanced module


Ipeds peer analysis system advanced module

  • From 2002 and 2003. According to the info button for 2004, these are the components: Finance, 2002 and 2003,from Public institutions - GASB 34/35: Fiscal year 2002 and 2003, from Expenses and other deductions, add current year totals for those 11 variables:


Calculated variables1
Calculated Variables 2002 and 2003. According to the info button for 2004, these are the components:

  • Create two summation variables

    • Core Expenses 2003

    • Core Expenses 2002

      using the 11 components for each year

  • Create a ratio variable

    • Instruction as a Percent of Core, 2004

      • Instruction – current year total as numerator

      • Core Expenses for 2004 as denominator


Recursive calculated variables
Recursive Calculated Variables 2002 and 2003. According to the info button for 2004, these are the components:

  • Create two ratio variables:

    • Instruction as a Percent of Core, 2003

    • Instruction as a Percent of Core, 2002

      using the same technique

      Why would you create a recursive variable instead of doing the calculation in Excel?

      So you can save it in a Multiple Variables List for use in the future!



Create an attractive report1
Create an Attractive Report fix them if they aren’t.

  • Add a report title

  • Adjust column widths and column titles

  • Order columns by year

  • Sort from high to low on ‘Instruction as a Percent of Core, 2002’

  • Create a graph to illustrate changes over three years


Research questions1
Research Questions fix them if they aren’t.

  • How many schools offer doctorates in Exercise Science?

  • How many doctorates in Exercise Science do they award?

    The Enrollment survey does not collect data by program, but Completions contains degrees awarded. Look at degrees awarded over a three-year period because not all schools with the program may award degrees every year.


Build master variables list1
Build Master Variables List fix them if they aren’t.

From 2003, 2004, 2005 Completions:

  • Qualifying variables:

    • CIP Code: 31.0505, Kinesiology and Exercise Science

    • Award Level: Doctor’s degree

    • First or Second major: First major

  • Variable:

    • Grand total


Comparison group strategy
Comparison Group Strategy fix them if they aren’t.

Because Exercise Science is a relatively small degree-producing program, you want to include in your sample all schools that awarded doctorates during a three-year period. That is, you want all schools that awarded doctorate in 2002-03 OR in 2003-04 OR in 2004-05, not just those that awarded doctorates in all three years—or only in 2004-05.


Define comparison group2
Define Comparison Group fix them if they aren’t.

From Master Variables List:

  • Select only Exercise Sci doctorates, 2002-03

    • Go to the query form;

    • Specify all schools with >0 degrees

    • 28 schools in comparison group

    • Accept and Continue

    • Add by Variable (from the Master Variables List)


Ipeds peer analysis system advanced module

  • Select fix them if they aren’t.only Exercise Sci doctorates, 2003-04

    • Go to the query form;

    • Specify all schools with >0 degrees

    • 28 schools in comparison group

    • Combine the two sets and eliminate duplicates

    • 31 schools in comparison group

    • Add by Variable (from the Master Variables List)


Ipeds peer analysis system advanced module

  • Select fix them if they aren’t.only Exercise Sci doctorates, 2004-05

    • Go to the query form;

    • Specify all schools with >0 degrees

    • 29 schools in comparison group

    • Combine the two sets and eliminate duplicates

    • 34 schools in comparison group

    • Examine the final list


Ipeds peer analysis system advanced module

Your sample contains 34 schools that awarded one or more doctorates in Exercise Science during one or more of the three years.


Run institutions data report1
Run Institutions Data Report doctorates in Exercise Science during one or more of the three years.

  • Select Reports and Stats, Institutions Data Report

  • From your Master Variables List, select all three years of Completions data

  • Specify long variable names

  • Download your results in csv format and save as an Excel file


Ipeds peer analysis system advanced module

Your raw data file should look like this. doctorates in Exercise Science during one or more of the three years.

Note that some schools did not award doctorates each year.


Create an attractive report2
Create an Attractive Report doctorates in Exercise Science during one or more of the three years.

  • Add a report title

  • Adjust column widths and column titles

  • Create a column for 3-year total

  • Sort from high to low on total degrees

  • Sum total degrees produced each year


Ipeds peer analysis system advanced module

You can print these results and distribute them! doctorates in Exercise Science during one or more of the three years.


Questions comments feedback
Questions? doctorates in Exercise Science during one or more of the three years.Comments?Feedback?