Advanced Peer Ananlysis System - CCSSE

Advanced Peer Ananlysis System - CCSSE

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 Average freshman tuition discount Expenditure comparison Schools offering a specific degree Data Available in the Peer 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 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 Year 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

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 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 1. Collection year vs. data year 2. Imputation and perturbation 3. Release sequence of IPEDS data 4. Structure of IPEDS data files 5. Frequently used/derived variables

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 Status by Survey Component 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 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 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

Its unpopularbut the alternative is data suppression Data Sharing Data that an institution puts into IPEDS

Data IN the IPEDS data collection system Belong to the institution May be shared BUT, may be subject to FERPA 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. Imputation

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 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 Single-record files contain one line of data for each institutionfor example, data in the Institutional Characteristics survey Multiple-record files contain several lines of data for each institutionfor example, data by race/ethnicity and gender in the Enrollment survey

Single-Record File unitid instnm stabbr obereg sector iclevel control affil hloffer 100654 ALABAMA A & M UNIVERSITY AL 5 1 1 1 -3 9 100663 UNIVERSITY OF ALABAMA AT BIRMINGHAM AL 5

1 1 1 -3 9 100690 SOUTHERN CHRISTIAN UNIVERSITY AL 5 2 1 2 -3 9 100706 UNIVERSITY OF ALABAMA IN HUNTSVILLE

AL 5 1 1 1 -3 9 100724 ALABAMA STATE UNIVERSITY AL 5 1 1 1 -3 8

100751 UNIVERSITY OF ALABAMA AL 5 1 1 1 -3 9 100812 ATHENS STATE UNIVERSITY AL 5 1 1 1 -3

5 100830 AUBURN UNIVERSITY-MONTGOMERY AL 5 1 1 1 -3 9 100858 AUBURN UNIVERSITY MAIN CAMPUS AL 5 1

1 1 -3 9 100937 BIRMINGHAM SOUTHERN COLLEGE AL 5 2 1 2 -3 7 101073 CONCORDIA COLLEGE AL

5 2 1 2 -3 5 101189 FAULKNER UNIVERSITY AL 5 2 1 2 -3 7

Multiple-Record File unitid 100654 100654 100654 100654 100654 100654 100654 100654 100654

100654 100654 100654 100663 100663 100663 100663 instnm idx_ef efrace01 efrace02 efrace03 efrace04 ALABAMA A & M UNIVERSITY -2

165 131 2282 2766 ALABAMA A & M UNIVERSITY -2 104 88 2082 2262 ALABAMA A & M UNIVERSITY -2

104 88 2082 2262 ALABAMA A & M UNIVERSITY -2 11 12 559 517 ALABAMA A & M UNIVERSITY -2

143 107 2037 2339 ALABAMA A & M UNIVERSITY -2 98 83 1960 2124 ALABAMA A & M UNIVERSITY -2

98 83 1960 2124 ALABAMA A & M UNIVERSITY -2 11 12 555 509 ALABAMA A & M UNIVERSITY -2

22 24 245 427 ALABAMA A & M UNIVERSITY -2 6 5 122 138 ALABAMA A & M UNIVERSITY -2

6 5 122 138 ALABAMA A & M UNIVERSITY -2 0 0 4 8 UNIVERSITY OF ALABAMA AT BIRMINGHAM -2

616 345 1084 2808 UNIVERSITY OF ALABAMA AT BIRMINGHAM -2 205 139 917 2262 UNIVERSITY OF ALABAMA AT BIRMINGHAM -2

200 128 839 2131 UNIVERSITY OF ALABAMA AT BIRMINGHAM -2 18 8 164 367 Qualifying Variables

When choosing variables from multiplerecord files, the user must first specify the qualifying variables The users choice tells PAS which records to select for the analysis 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. Then select Hispanic men and Hispanic women.

The resulting PAS file will contain a value for each possible combination: 5. 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! Review of strategies Analysis 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: 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 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 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 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 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 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 http://nces.ed.gov/ipeds Select the Peer Analysis System

Login at the Institution level, which includes early release data with missing values not yet imputed. 1. Enter User ID (an IPEDS UnitID) 2. Enter Password

(same UnitID) 3. Click the Login button You can use your institutions UnitID or choose another. Find other UnitIDs using IPEDS Cool.

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. Click on Main Menu whenever you want to see a Session Summary or to access your Master Variables List. Research 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 institutions average tuition. Calculation 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 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 Sources Constraint: The most recent financial aid data is 2003-04, so all variables should be selected for this year. Define 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 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 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 Do 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 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 Add a title, modify the headings, and format the numbers. Its a report! Research 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 Group Add by Variable From Institutional Characteristics, 2004, add State abbreviation Sector of institution

Carnegie Classification code Query Form Comparison Group Add 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 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 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 arent. Create 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 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 List From 2003, 2004, 2005 Completions: Qualifying variables: CIP Code: 31.0505, Kinesiology and Exercise Science Award Level: Doctors degree First or Second major: First major Variable: Grand total

Comparison 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 200304 OR in 2004-05, not just those that awarded doctorates in all three yearsor only in 2004-05. Define 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.

Run 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.

Note that some schools did not award doctorates each year. Create 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! Questions? Comments? Feedback?

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