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Using the IEA IDB Analyzer Correlations & Regression

Using the IEA IDB Analyzer Correlations & Regression. 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

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Using the IEA IDB Analyzer Correlations & Regression

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  1. Using the IEA IDB Analyzer Correlations & Regression

  2. 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

  3. 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

  4. Calculating Correlations • 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

  5. Select Variable of Interest Student Questionnaire, Q14A-F, p. 13 Variables of Interest: PARTCOM PVCIV01-05

  6. The Analysis File • 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

  7. Correlations - Preparation • 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)

  8. Correlations - Details Select Analysis FileC:\ICCS2009\Work\ICG_ISG_INTC2.sav

  9. Correlations - Details 1) Select Correlations 2) Check Exclude Missing from Analysis 3) Check With Achievement Scores

  10. Correlations - Details IDCNTRY TOTWGTS JKZONES

  11. Correlations - Details Search for PARTCOM

  12. Correlations - Details Search results will be displayed

  13. Correlations - Details Highlight variable Use arrow key to add variable to analysis

  14. Correlations - Details

  15. Correlations - Details Highlight variable Use arrow key to add variable to analysis

  16. Correlations - Details Define path and filename for output:“C:\ICCS2009\Work\Table_5_09.*” Change number of decimals to “1”

  17. Correlations - Details • The IDB Analyzer creates SPSS Syntax and starts SPSS • In SPSS Syntax Editor Choose: Run > All

  18. 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)

  19. Correlations – SPSS Output

  20. Correlations – Excel Output

  21. Correlations – Excel Output Achievement Scores Mean Achievement List of Countries Sum of Weights S.E. of Mean Achievement

  22. Correlations – Excel Output Correlation of PV with itself S.E. of Correlation Standard Deviation of Mean Achievement S.E. of Standard Deviation of Mean Achievement

  23. Correlations – Excel Output S.E. of Mean of Variable S.E. of Standard Deviation of Mean of Variable Variable Name of Second Variable Mean of Variable (here: Country Mean) Standard Deviation of Mean of Variable

  24. Correlations – Excel Output Correlation of variable 1 with variable 2(here: Achievement with Participation in Community) S.E. of Correlation

  25. Correlations – Excel Output

  26. 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

  27. 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

  28. Linear Regression Model

  29. Linear Regression Model • yis the dependent variable – here: estimated mean of all 5 plausible values • x is the independent variable • ß0is the intercept (value of ywhen x is zero) • ß1 is the slope (change in yfor each unit increase in x) x = + × y β β 0 1

  30. Computing Regression • 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

  31. Computing Regression • 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

  32. 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

  33. Dummy Coding for Regression IMMIG  Reg01IMMIG

  34. Dummy Coding for Regression • IMMIG values: 0 1 1 System Missing

  35. SPSS: Dummy Coding for Regression Menu: TRANSFORM  Recode into Different Variables...

  36. SPSS: Dummy Coding for Regression Menu: TRANSFORM  Recode into Different Variables... 1  0 2  1 3  1 ELSE  SYSMISS

  37. Linear Regression Model Predictor variable: Reg01IMMIG x = + × y β β 0 1 Mean achievement for native students Difference between mean achieve-ment of native and mean achieve-ment of non-native students

  38. The Analysis File • 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

  39. 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)

  40. Regression - Details C:\ICCS2009\Work\ICG_ISG_INTC2.sav 1) Select Regression2) Check Exclude Missing from Analysis3) Check With Achievement Scores IDCNTRY Reg01IMMIG PVICIV01-05 Change the number of decimals to 2 TOTWGTS JKZONES C:\ICCS2009\Work\Table_7_1.*

  41. Regression - Details • The IDB Analyzer creates SPSS Syntax and starts SPSS • In SPSS Syntax Editor Choose: Run > All

  42. 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

  43. Regression – SPSS Output Number of Cases S.E. of Intercept Multiple R-Squared Intercept: Mean Achievement of Native Students

  44. Regression – SPSS Output Estimate of Regression Coefficient S.E. of Regression Coefficient T-Statistics of Regression Coefficient

  45. Regression – SPSS Output ABS (-1.3) < 1.96 In Bulgaria the difference in civic knowledge between native students and non-native students is NOT significant.

  46. Regression – SPSS Output ABS (-8.9) > 1.96 In Austria the difference in civic knowledge between native students and non-native students IS significant.

  47. Regression – SPSS Output Differences in Draft Table 7.1 of Int. Report are incorrect

  48. Regression – SPSS Output x = - 516,2 × y 56,6 Predictor variable: Reg01IMMIG Mean achievement for native students Difference between mean achieve-ment of native and mean achieve-ment of non-native students

  49. Thank you for your attention! Any Questions?

  50. 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

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