ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Using the IEA IDB Analyzer Correlations & Regression.

Slides:



Advertisements
Similar presentations
MICS Data Processing Workshop
Advertisements

MICS4 Data Processing Workshop Multiple Indicator Cluster Surveys Data Processing Workshop Creating Analysis Files: Description of Preparation Steps.
Prerequisites Recommended modules to complete before viewing this module 1. Introduction to the NLTS2 Training Modules 2. NLTS2 Study Overview 3. NLTS2.
1 Interpreting a Model in which the slopes are allowed to differ across groups Suppose Y is regressed on X1, Dummy1 (an indicator variable for group membership),
Applied Econometrics Second edition
ICCS 2009 IDB Seminar – Nov 24-26, 2010 – IEA DPC, Hamburg, Germany Using the IEA IDB Analyzer to merge and analyze data.
ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Using the IEA IDB Analyzer to merge and analyze data.
© McGraw-Hill Higher Education. All Rights Reserved. Chapter 2F Statistical Tools in Evaluation.
Introduction to SPSS Allen Risley Academic Technology Services, CSUSM
Some Terms Y =  o +  1 X Regression of Y on X Regress Y on X X called independent variable or predictor variable or covariate or factor Which factors.
1 Module II Lecture 4:F-Tests Graduate School 2004/2005 Quantitative Research Methods Gwilym Pryce
A Simple Guide to Using SPSS© for Windows
Basic Business Statistics, 11e © 2009 Prentice-Hall, Inc. Chap 15-1 Chapter 15 Multiple Regression Model Building Basic Business Statistics 11 th Edition.
1 1 Slide © 2003 South-Western/Thomson Learning™ Slides Prepared by JOHN S. LOUCKS St. Edward’s University.
Multiple Regression Research Methods and Statistics.
Introduction to SPSS Short Courses Last created (Feb, 2008) Kentaka Aruga.
Week 14 Chapter 16 – Partial Correlation and Multiple Regression and Correlation.
Social Science Research Design and Statistics, 2/e Alfred P. Rovai, Jason D. Baker, and Michael K. Ponton Internal Consistency Reliability Analysis PowerPoint.
FEBRUARY, 2013 BY: ABDUL-RAUF A TRAINING WORKSHOP ON STATISTICAL AND PRESENTATIONAL SYSTEM SOFTWARE (SPSS) 18.0 WINDOWS.
Introduction to SPSS (For SPSS Version 16.0)
The Usage of IDB Analyzer: From our Research on Homework Saki Ikoma Penn State EDTHP
Introduction to Linear Regression and Correlation Analysis
How to Analyze Data? Aravinda Guntupalli. SPSS windows process Data window Variable view window Output window Chart editor window.
Using PISA data in performance audit: Schooling of immigrant students in Finland Dr. Tanja Kirjavainen National Audit Office of Finland 8 th meeting of.
1 Experimental Statistics - week 4 Chapter 8: 1-factor ANOVA models Using SAS.
Managerial Economics Demand Estimation. Scatter Diagram Regression Analysis.
Statistics for the Social Sciences Psychology 340 Fall 2013 Correlation and Regression.
Copyright © 2010, 2007, 2004 Pearson Education, Inc. All Rights Reserved Section 10-5 Multiple Regression.
Multilevel Linear Models Field, Chapter 19. Why use multilevel models? Meeting the assumptions of the linear model – Homogeneity of regression coefficients.
C opyright  2007 by Oxford University Press, Inc. PowerPoint Slides Prepared by Robert F. Brooker, Ph.D.Slide 1 1.
Part IV Significantly Different Using Inferential Statistics Chapter 15 Using Linear Regression Predicting Who’ll Win the Super Bowl.
Part IV Significantly Different: Using Inferential Statistics
ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Using the IEA IDB Analyzer Percentages & Means.
Perform Descriptive Statistics Section 6. Descriptive Statistics Descriptive statistics describe the status of variables. How you describe the status.
Chapter 13 Multiple Regression
Simple & Multiple Regression 1: Simple Regression - Prediction models 1.
ICCS 2009 IDB Workshop, 18 th February 2010, Madrid 1 Training Workshop on the ICCS 2009 database Weighting and Variance Estimation picture.
General Linear Model.
Mr. Magdi Morsi Statistician Department of Research and Studies, MOH
Lecture 5 EPSY 642 Victor Willson Fall EFFECT SIZE DISTRIBUTION Hypothesis: All effects come from the same distribution What does this look like.
PSC 47410: Data Analysis Workshop  What’s the purpose of this exercise?  The workshop’s research questions:  Who supports war in America?  How consistent.
DTC Quantitative Methods Summary of some SPSS commands Weeks 1 & 2, January 2012.
Lesson 14 - R Chapter 14 Review. Objectives Summarize the chapter Define the vocabulary used Complete all objectives Successfully answer any of the review.
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin Simple Linear Regression Analysis Chapter 13.
ICCS 2009 IDB Seminar – Nov 24-26, 2010 – IEA DPC, Hamburg, Germany Training Workshop on the ICCS 2009 database Weights and Variance Estimation picture.
Today Introduction to Stata – Files / directories – Stata syntax – Useful commands / functions Logistic regression analysis with Stata – Estimation – GOF.
Using SPSS Note: The use of another statistical package such as Minitab is similar to using SPSS.
© Copyright 2000, Julia Hartman 1 An Interactive Tutorial for SPSS 10.0 for Windows © Analysis of Covariance (Regression Approach) by Julia Hartman Next.
1 SPSS MACROS FOR COMPUTING STANDARD ERRORS WITH PLAUSIBLE VALUES.
MICS4 Data Processing Workshop Multiple Indicator Cluster Surveys Data Processing Workshop Tabulation Programs.
IENG-385 Statistical Methods for Engineers SPSS (Statistical package for social science) LAB # 1 (An Introduction to SPSS)
Chapter 11 REGRESSION Multiple Regression  Uses  Explanation  Prediction.
Topics Introduction to Stata – Files / directories – Stata syntax – Useful commands / functions Logistic regression analysis with Stata – Estimation –
Chapter 15 Multiple Regression Model Building
Econ 326 Prof. Mariana Carrera Lab Session X [DATE]
PowerPoint Slides Prepared by Robert F. Brooker, Ph.D. Slide 1
Dr. Siti Nor Binti Yaacob
DEPARTMENT OF COMPUTER SCIENCE
Multiple Regression.
Week 14 Chapter 16 – Partial Correlation and Multiple Regression and Correlation.
Multiple Regression Example
Dr. Siti Nor Binti Yaacob
S519: Evaluation of Information Systems
Simple Linear Regression
Introduction to Logistic Regression
ADVANCED DATA ANALYSIS IN SPSS AND AMOS
24/02/11 Tutorial 2 Inferential Statistics, Statistical Modelling & Survey Methods (BS2506) Pairach Piboonrungroj (Champ)
Regression Analysis.
Finding Correlation Coefficient & Line of Best Fit
Chapter 9 Excel Extension: Now You Try!
Presentation transcript:

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Using the IEA IDB Analyzer Correlations & Regression

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Table of content Correlations –Settings for the Analysis –Running the Analysis –Compare SPSS Output and International Report –Output in MS Excel Regression –Linear Regression Model –Settings for the Analysis –Running the Analysis –Compare SPSS Output and International Report –Output in MS Excel Hands-On Training

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Table of content Correlations –Settings for the Analysis –Running the Analysis –Compare SPSS Output and International Report –Output in MS Excel Regression –Linear Regression Model –Settings for the Analysis –Running the Analysis –Compare SPSS Output and International Report –Output in MS Excel Hands-On Training

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Choose variable(s) to be analyzed Load the SPSS Analysis File Choose Correlations as analysis type (some settings will be done automatically with respect to the datafile and the analysis method chosen) Select Variables from the datafile to be analyzed as Analysis Variables Define location and name of the Output Files Start SPSS and run analysis Calculating Correlations

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Student Questionnaire, Q14A-F, p. 13 Variables of Interest: PARTCOM PVCIV01-05 Select Variable of Interest

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid The analysis file needs to be loaded from the respective directory Countries in the example analysis file: –Austria –Belgium (Flemish) –Bulgaria –Denmark –England –Estonia –Finland The Analysis File

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Select Analysis File: C:\ICCS2009\Work\ICG_ISG_INTC2.sav Select Analysis Type: Correlations Select Analysis Variables: PARTCOM(Students’ civic participation in the wider community) Select Achievement Variables: PVICIV01-05 (Table 5.09 from ICCS2009 International report, first column) Correlations - Preparation

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Select Analysis File C:\ICCS2009\Work\ICG_ISG_INTC2.sav Correlations - Details

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Correlations - Details 1) Select Correlations 2) Check Exclude Missing from Analysis 3) Check With Achievement Scores

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Correlations - Details TOTWGTS JKZONES IDCNTRY

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Correlations - Details Search for PARTCOM

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Correlations - Details Search results will be displayed

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Correlations - Details Highlight variable Use arrow key to add variable to analysis

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Correlations - Details

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Highlight variable Use arrow key to add variable to analysis Correlations - Details

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Correlations - Details Define path and filename for output: “C:\ICCS2009\Work\Table_5_09.*” Change number of decimals to “1”

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Correlations - Details The IDB Analyzer creates SPSS Syntax and starts SPSS In SPSS Syntax Editor Choose: Run > All

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Correlations - Outcome As a result the IDB Analyzer creates the following in the working directory (C:\ICCS2009\Work\): –SPSS Syntax file – contains the syntax with the commands (*.sps) –SPSS Data file – contains statistics from the analysis (*.sav) –MS Excel Output file – contains statistics from the analysis (*.xls)

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Correlations – SPSS Output

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Correlations – Excel Output

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Correlations – Excel Output List of Countries Achievement Scores Sum of Weights Mean Achievement S.E. of Mean Achievement

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Correlations – Excel Output Standard Deviation of Mean Achievement S.E. of Standard Deviation of Mean Achievement Correlation of PV with itself S.E. of Correlation

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Correlations – Excel Output Variable Name of Second Variable Mean of Variable (here: Country Mean) S.E. of Mean of Variable Standard Deviation of Mean of Variable S.E. of Standard Deviation of Mean of Variable

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Correlations – Excel Output Correlation of variable 1 with variable 2 (here: Achievement with Participation in Community) S.E. of Correlation

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Correlations – Excel Output

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Table of content Correlations –Settings for the Analysis –Running the Analysis –Compare SPSS Output and International Report –Output in MS Excel Regression –Linear Regression Model –Settings for the Analysis –Running the Analysis –Compare SPSS Output and International Report –Output in MS Excel Hands-On Training

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Table of content Correlations –Settings for the Analysis –Running the Analysis –Compare SPSS Output and International Report –Output in MS Excel Regression –Linear Regression Model –Settings for the Analysis –Running the Analysis –Compare SPSS Output and International Report –Output in MS Excel Hands-On Training

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Linear Regression Model

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Linear Regression Model y is the dependent variable – here: estimated mean of all 5 plausible values x is the independent variable ß 0 is the intercept (value of y when x is zero) ß 1 is the slope (change in y for each unit increase in x) 10 ββ   x y

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Can be used to calculate regression coefficients and their (jackknifed) standard errors for the ICCS background variables Uses the jackknifing procedure and therefore considers the sampling method used in ICCS Makes use of the variables JKZONE and JKREP Computing Regression

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Choose variable to be analyzed Load the SPSS Analysis File Choose Regression as analysis type (some settings will be done automatically) Select Variables from the datafile to be analyzed as Analysis Variable AND/OR Select the plausible values as Achievement Scores Define location and name of the Output Files Start SPSS and run analysis Computing Regression

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Recoding variables Some tables might display data differently than in the data files E.g., table 7.1 has been calculated using dummy recoded information of the students‘ immigration background (variable name in the datafile is IMMIG) For replication of the table, the information from the variable IMMIG needs to be recoded in SPSS and added as a new variable to the datafile before running the analysis

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Native 1st Generation Immigrant Non-Native IMMIG 123 Reg01IMMIG 011 Dummy Coding for Regression IMMIG  Reg01IMMIG

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Dummy Coding for Regression IMMIG values: System Missing 0 1 1

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Menu: TRANSFORM  Recode into Different Variables... SPSS: Dummy Coding for Regression

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid SPSS: Dummy Coding for Regression 1  0 2  1 3  1 ELSE  SYSMISS Menu: TRANSFORM  Recode into Different Variables...

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid 10 ββ   x y Linear Regression Model Predictor variable: Reg01IMMIG Mean achievement for native students Difference between mean achieve- ment of native and mean achieve- ment of non-native students

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid The analysis file needs to be loaded from the respective directory Countries in the example analysis file: –Austria –Belgium (Flemish) –Bulgaria –Denmark –England –Estonia –Finland The Analysis File

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Computing Regression Select data file: C:\ICCS2009\Work\ICG_ISG_INTC2_Reg.sav Analysis Type: Regression Grouping Variable: IDCNTRY Analysis Variable: Reg01IMMIG Achievement Scores: PVICIV01-05 (Table 7.1, first column from ICCS2009 International report)

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid IDCNTRY TOTWGTS JKZONES C:\ICCS2009\Work\ICG_ISG_INTC2.savChange the number of decimals to 2 C:\ICCS2009\Work\Table_7_1.* Reg01IMMIG PVICIV ) Select Regression 2) Check Exclude Missing from Analysis 3) Check With Achievement Scores Regression - Details

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Regression - Details The IDB Analyzer creates SPSS Syntax and starts SPSS In SPSS Syntax Editor Choose: Run > All

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Regression - Outcome As a result IDB Analyzer creates the following in the working directory (C:\ICCS2009\Work): –SPSS Syntax file – contains the syntax with the commands –SPSS Data file – contains statistics from the analysis –MS Excel Output file – contains statistics from the analysis

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Regression – SPSS Output Number of Cases Multiple R-Squared Intercept: Mean Achievement of Native Students S.E. of Intercept

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Regression – SPSS Output Estimate of Regression Coefficient S.E. of Regression Coefficient T-Statistics of Regression Coefficient

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Regression – SPSS Output In Bulgaria the difference in civic knowledge between native students and non-native students is NOT significant. ABS (-1.3) < 1.96

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Regression – SPSS Output In Austria the difference in civic knowledge between native students and non-native students IS significant. ABS (-8.9) > 1.96

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Regression – SPSS Output Differences in Draft Table 7.1 of Int. Report are incorrect

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Regression – SPSS Output 56,6 516,2   x y Predictor variable: Reg01IMMIG Mean achievement for native students Difference between mean achieve- ment of native and mean achieve- ment of non-native students

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Any Questions? Thank you for your attention!

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Table of content Correlations –Settings for the Analysis –Running the Analysis –Compare SPSS Output and International Report –Output in MS Excel Regression –Linear regression Model –Settings for the Analysis –Running the Analysis –Compare SPSS Output and International Report –Output in MS Excel Hands-On Training

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Table of content Correlations –Settings for the Analysis –Running the Analysis –Compare SPSS Output and International Report –Output in MS Excel Regression –Linear regression Model –Settings for the Analysis –Running the Analysis –Compare SPSS Output and International Report –Output in MS Excel Hands-On Training

ICCS 2009 IDB Workshop, 18 th February 2010, Madrid Hands-On Training A.Re-produce the example using your country data - Correlation of students’ participation in the wider community with civic and citizenship achievement (PVCIV01-05 with PARTCOM) and/or B.Re-produce the example using your country data - Regression of students’ immigration status on civic and citizenship achievement of (IMMIG [recoded] on PVCIV01-05) and/or C.Practice with own selected variables following these analysis steps