using the iea idb analyzer correlations & regression

ICCS 2009 IDB Workshop, 18th February 2010, Madrid

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– Compare SPSS Output and International Report– Output in MS Excel

Hands-On Training


Choose variable(s) to be analyzed Load the SPSS Analysis FileChoose 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 VariablesDefine location and name of the Output FilesStart SPSS and run analysis

Calculating Correlations


Student Questionnaire, Q14A-F, p. 13Variables of Interest: PARTCOM

PVCIV01-05

Select Variable of Interest


The analysis file needs to be loaded from the respective directoryCountries in the example analysis file:– Austria– Belgium (Flemish)– Bulgaria– Denmark– England– Estonia– Finland

The Analysis File


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


Select Analysis FileC:\ICCS2009\Work\ICG_ISG_INTC2.sav

Correlations - Details



1) Select Correlations 2) Check Exclude Missing from Analysis 3) Check With Achievement Scores



TOTWGTS

JKZONES

IDCNTRY



Search for PARTCOM



Search results will be displayed



Highlight variable

Use arrow key to add variable to

analysis



Define path and filename for output:

“C:\ICCS2009\Work\Table_5_09.*”

Change number of decimals to “1”



The IDB Analyzer creates SPSS Syntax and starts SPSSIn SPSS Syntax Editor Choose: Run > All


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)


Correlations – SPSS Output


Correlations – Excel Output



List of Countri

es

Achievement Scores

Sum of Weight

s

Mean Achievemen

t

S.E. of Mean Achievemen

t



Standard Deviation of Mean

Achievement

S.E. of Standard Deviation of Mean

Achievement

Correlation of PV with

itself

S.E. of Correlation



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



Correlation of variable 1 with variable 2(here: Achievement with Participation in

Community)

S.E. of Correlation


Table of content


Regression– Linear Regression Model– Settings for the Analysis– Running the Analysis– Compare SPSS Output and International Report– Output in MS Excel

Hands-On Training


Linear Regression Model



y is the dependent variable – here: estimated mean of all 5 plausible valuesx is the independent variableß0 is the intercept (value of y when x is zero)ß1 is the slope (change in y for each unit increase in x)

10 ββ ×+= xy


Can be used to calculate regression coefficients and their (jackknifed) standard errors for the ICCS background variablesUses the jackknifing procedure and therefore considers the sampling method used in ICCSMakes use of the variables JKZONE and JKREP

Computing Regression


Choose variable to be analyzed Load the SPSS Analysis FileChoose 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 ScoresDefine location and name of the Output FilesStart SPSS and run analysis

Computing Regression


Recoding variablesSome tables might display data differently than in the data filesE.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


Native1st

Generation Immigrant

Non-Native

IMMIG 1 2 3Reg01IMMIG 0 1 1

Dummy Coding for Regression

IMMIG Reg01IMMIG


Dummy Coding for RegressionIMMIG values:

System Missing

011


Menu: TRANSFORM Recode into Different Variables...

SPSS: Dummy Coding for Regression


SPSS: Dummy Coding for Regression

1 02 13 1ELSE SYSMISS

Menu: TRANSFORM Recode into Different Variables...


10 ββ ×+= xy


Predictor variable: Reg01IMMIG

Mean achievement for native students

Difference between mean achieve-ment of native and mean achieve-ment of non-

native students


The analysis file needs to be loaded from the respective directoryCountries in the example analysis file:– Austria– Belgium (Flemish)– Bulgaria– Denmark– England– Estonia– Finland

The Analysis File


Computing RegressionSelect data file:

C:\ICCS2009\Work\ICG_ISG_INTC2_Reg.savAnalysis Type:

RegressionGrouping Variable:

IDCNTRYAnalysis Variable:

Reg01IMMIGAchievement Scores:

PVICIV01-05 (Table 7.1, first column from ICCS2009 International report)


IDCNTRY

TOTWGTSJKZONES

C:\ICCS2009\Work\ICG_ISG_INTC2.sav

Change the number of

decimals to 2

C:\ICCS2009\Work\Table_7_1.*

Reg01IMMIGPVICIV01-05

1) Select Regression2) Check Exclude Missing from Analysis3) Check With Achievement Scores

Regression - Details


Regression - DetailsThe IDB Analyzer creates SPSS Syntax and starts SPSSIn SPSS Syntax Editor Choose: Run > All


Regression - OutcomeAs 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


Regression – SPSS Output

Number of Cases

Multiple R-Squared

Intercept: Mean

Achievement of Native Students

S.E. of Intercept



Estimate of Regression Coefficient

S.E. of Regression Coefficient

T-Statistics of

Regression Coefficient



In Bulgaria the difference in civic knowledge between native students and non-native students is NOT significant.

ABS (-1.3) < 1.96



In Austria the difference in civic knowledge between native students and non-native students IS significant.

ABS (-8.9) > 1.96



Differences in Draft Table 7.1 of Int.

Report are incorrect



56,6516,2 ×-= xy

Predictor variable: Reg01IMMIG

Mean achievement for native students

Difference between mean achieve-ment of native and mean achieve-ment of non-

native students


Any Questions?

Thank you for your attention!


Table of content


Regression– Linear regression Model– Settings for the Analysis– Running the Analysis– Compare SPSS Output and International Report– Output in MS Excel

Hands-On Training


Hands-On TrainingA. 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/orB. 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

using the iea idb analyzer correlations & regression

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