IPEDSIPEDSPeer Analysis SystemPeer Analysis System

Advanced ModuleAdvanced Module

TheThe place to go for place to go for IPEDS data:IPEDS data:

http://nces.ed.gov/ipeds

Session AgendaSession Agenda■ Data availability and issuesData availability and issues

■ Important data conceptsImportant data concepts

■ Review of Peer Analysis SystemReview of Peer Analysis System─ BasicsBasics─ Advanced featuresAdvanced features

■ Research Questions with PASResearch Questions with PAS─ Average freshman tuition discountAverage freshman tuition discount─ Expenditure comparisonExpenditure comparison─ Schools offering a specific degreeSchools offering a specific degree

Data Available in theData Available in thePeer Analysis SystemPeer 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 CaveatsAvailability 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 Availability by YearData Availability by Year

Data IssuesData 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 IssuesMore 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 ConceptsImportant Data Concepts

1.1. Collection year vs. data yearCollection year vs. data year

2.2. Imputation and perturbationImputation and perturbation

3.3. Release sequence of IPEDS dataRelease sequence of IPEDS data

4.4. Structure of IPEDS data filesStructure of IPEDS data files

5.5. Frequently used/derived variablesFrequently used/derived variables

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

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

1.1. Collection Year vs. Data Year Collection Year vs. Data Year

Status by Survey ComponentStatus by Survey Component

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

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

Master Variables List SelectionMaster Variables List Selection

2.2. Disclosure Disclosure ProtectionProtection■ 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

PerturbationPerturbation■ 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 SharingData 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

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

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

ImputationImputation■ 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

3.3. Data Release Stages 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

4.4. Structure of IPEDS Data Files 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 FileSingle-Record Fileunitid instnm stabbr obereg sector iclevel control affil hloffer100654 ALABAMA A & M UNIVERSITY AL 5 1 1 1 -3 9100663 UNIVERSITY OF ALABAMA AT BIRMINGHAMAL 5 1 1 1 -3 9100690 SOUTHERN CHRISTIAN UNIVERSITYAL 5 2 1 2 -3 9100706 UNIVERSITY OF ALABAMA IN HUNTSVILLEAL 5 1 1 1 -3 9100724 ALABAMA STATE UNIVERSITY AL 5 1 1 1 -3 8100751 UNIVERSITY OF ALABAMA AL 5 1 1 1 -3 9100812 ATHENS STATE UNIVERSITY AL 5 1 1 1 -3 5100830 AUBURN UNIVERSITY-MONTGOMERYAL 5 1 1 1 -3 9100858 AUBURN UNIVERSITY MAIN CAMPUSAL 5 1 1 1 -3 9100937 BIRMINGHAM SOUTHERN COLLEGEAL 5 2 1 2 -3 7101073 CONCORDIA COLLEGE AL 5 2 1 2 -3 5101189 FAULKNER UNIVERSITY AL 5 2 1 2 -3 7

Multiple-Record FileMultiple-Record Fileunitid instnm idx_ef efrace01 efrace02 efrace03 efrace04100654 ALABAMA A & M UNIVERSITY -2 165 131 2282 2766100654 ALABAMA A & M UNIVERSITY -2 104 88 2082 2262100654 ALABAMA A & M UNIVERSITY -2 104 88 2082 2262100654 ALABAMA A & M UNIVERSITY -2 11 12 559 517100654 ALABAMA A & M UNIVERSITY -2 143 107 2037 2339100654 ALABAMA A & M UNIVERSITY -2 98 83 1960 2124100654 ALABAMA A & M UNIVERSITY -2 98 83 1960 2124100654 ALABAMA A & M UNIVERSITY -2 11 12 555 509100654 ALABAMA A & M UNIVERSITY -2 22 24 245 427100654 ALABAMA A & M UNIVERSITY -2 6 5 122 138100654 ALABAMA A & M UNIVERSITY -2 6 5 122 138100654 ALABAMA A & M UNIVERSITY -2 0 0 4 8100663 UNIVERSITY OF ALABAMA AT BIRMINGHAM-2 616 345 1084 2808100663 UNIVERSITY OF ALABAMA AT BIRMINGHAM-2 205 139 917 2262100663 UNIVERSITY OF ALABAMA AT BIRMINGHAM-2 200 128 839 2131100663 UNIVERSITY OF ALABAMA AT BIRMINGHAM-2 18 8 164 367

Qualifying VariablesQualifying Variables

■ 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

Level of student is the qualifying variable that lets you to choose. Here, choose Full-time students total and Part-time students total.

Level of student is the qualifying variable that lets you to choose. Here, choose Full-time students total and Part-time students total.

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

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

Then select Hispanic men and Hispanic women.Then select Hispanic men and Hispanic women.

The resulting PAS file will contain a value for each The resulting PAS file will contain a value for each possible combination:possible combination:

5.5. Frequently Used/Derived Variables 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 SystemThe Peer Analysis Systemis the fastest way to captureis the fastest way to capture

IPEDS data for your analyses!IPEDS data for your analyses!

Review of strategiesReview of strategies

Analysis StrategyAnalysis Strategy

■ 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:

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 GroupComparison Group■ 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 & StatsTypes of Analyses = Reports & Stats■ 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 ListMaster Variables List

■ 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 VariablesCalculated Variables

■ 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 SessionSupport During Your Session■ 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 Log On to the Peer Analysis SystemPeer Analysis System

http://nces.ed.gov/ipeds

Select the Peer Analysis System

Select the Peer Analysis System

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

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

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

Find other UnitIDs using IPEDS Cool.

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

Find other UnitIDs using IPEDS Cool.

1. Enter User ID (an IPEDS UnitID)

2. Enter Password (same UnitID)

3. Click the Login button

1. Enter User ID (an IPEDS UnitID)

2. Enter Password (same UnitID)

3. Click the Login button

You can use your own institution as LinchPin,

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

You can use your own institution as LinchPin,

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

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

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.

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

Research QuestionResearch Question■ 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 StrategyCalculation Strategy

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 RequiredVariables Required

■ 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 SourcesIPEDS Survey Sources

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

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

Define Comparison GroupDefine Comparison Group

■ 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 ListBuild 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)

■ From Enrollments, 2003,from Total entering class: Fall 2003,add─Full-time first-time degree/certificate-seeking

undergraduate (current years GRS cohort)

■ From Student Financial Aid, 2004,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 ReportRun Institutions Data Report

■ 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

…and it looks like this…and it looks like this

Do Calculations in ExcelDo Calculations in Excel

■ 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 ReportCreate an Attractive Report

■ Add a report title

■ Adjust column widths and column titles

■ Sort from high to low on average freshman discount rate

-Total Tuition Revenue-Total Grant Aid- Freshman Discount Rate

-Total Tuition Revenue-Total Grant Aid- Freshman Discount Rate

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

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

Research QuestionsResearch Questions

■ 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 GroupDefine Comparison Group

■ Add by Variable

■ From Institutional Characteristics, 2004, add─State abbreviation─Sector of institution─Carnegie Classification code

Query FormQuery Form

Comparison GroupComparison Group

Add to Master Variables ListAdd to 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

■ ‘Core expenses, total dollar’ must be calculated for 2002 and 2003. According to the info button for 2004, these are the components:

■ From 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 VariablesCalculated Variables■ 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 VariablesRecursive Calculated Variables■ 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!

Check to see if the columns are in chronological order, and fix them if they aren’t.

Check to see if the columns are in chronological order, and fix them if they aren’t.

Create an Attractive ReportCreate an Attractive Report

■ 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 QuestionsResearch Questions

■ 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 ListBuild Master Variables List

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 StrategyComparison Group Strategy

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 GroupDefine Comparison Group

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)

■ Select 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)

■ Select 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

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

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 ReportRun Institutions Data Report

■ 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

Your raw data file should look like this.

Your raw data file should look like this.

Note that some schools did not award doctorates each year.

Note that some schools did not award doctorates each year.

Create an Attractive ReportCreate an Attractive Report

■ 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

You can print these results and distribute them!

You can print these results and distribute them!

Questions?Questions?Comments?Comments?Feedback?Feedback?