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Data Lab #8 July 23, 2008 Ivan Katchanovski, Ph.D. POL 242Y-Y Multiple Regression: SPSS Commands • SPSS Command: Analyze-Regression-Linear • “Dependent” box: Select the dependent variable • “Independent” box: Select independent variables • Method: “Enter” • Statistics: – “Estimates” of “Regression Coefficients” – “Model fit” 2 Example: Multiple Research Hypotheses • First Research Hypothesis: The level of economic development has a positive effect on the level of democracy • Second Research Hypothesis: Former British colonies are more likely to be democratic compared to other countries • Third Research Hypothesis: Protestant countries are more likely to be democratic compared to other countries • Dataset: World 3 Example: Variables • Dependent Variable: – Freedom House democracy rating reversed: • Interval-ratio • Independent Variables: – GDP per capita ($1000) • Interval-ratio • Colony variable – Nominal – Has to be transformed into dummy variables • Religious culture variable – Nominal – Has to be transformed into dummy variables 4 Example: Dummy Independent Variables • Former British colony – Recode into new variable: UK=1; All other values=0 – Omitted from multiple regression • Former French colony – Recode into new variable: France=1; All other values=0 • Former Spanish colony – Recode into new variable: Spain=1; All other values=0 • Other countries – Recode into new variable: UK, France, Spain=0; All other values=1 5 Example: Dummy Independent Variables • Protestant – Recode into new variable: Protestant=1; All other values=0 – Omitted from regression • Roman Catholic – Recode into new variable: Catholic=1; All other values=0 • Muslim – Recode into new variable: Muslim=1; All other values=0 • Other – Recode into new variable: Protestant, Catholic, Muslim=0; All other values=1 6 Table: Determinants of democracy GDP per cap ($1000) French colony Spanish colony Other country Catholic Muslim Other religion Constant Adjusted R square N Unstandardized regression coefficients (Standard error) .199*** (.027) -.885* (.353) .038 (.308) .196 (.409) 1.008** (.296) -.257 (1.300) .747* (.329) 3.660*** (.289) .481 Standardized regression coefficients .563 -.204 .011 .042 .284 -.014 .178 111 *** Statistically significant at the .001 level, ** statistically significant at the .01 level, * statistically significant at the .05 level 7 Example: Statistical Significance • Number of cases: N=111 • .1 or 10% significance level can be used • Regression coefficient of the GDP variable: • SPSS: p(obtained)=.000 <p(critical)=.001=.1% • Statistically significant at the .001 or .1% level • Regression coefficient of the French colony variable: • SPSS: p(obtained)=.014<p(critical)=.05 • Statistically significant at the .05 or 5% level • Regression coefficient of the Catholic country variable: • SPSS: p(obtained)=.001<p(critical)=.01 • Statistically significant at the .01 or 1% level 8 Example: Statistical Significance • Regression coefficient of the Other religion variable: • SPSS: p(obtained)=.025<p(critical)=.05 • Statistically significant at the .05 or 5% level • Regression coefficient of the Constant: • SPSS: p(obtained)=.000<p(critical)=.001 • Statistically significant at the .001 or .1% level – Regression coefficients of all other variables: • SPSS: p(obtained) ranges from .634 to .902>p(critical)=.1 • Statistically insignificant – Statistical significance of the regression model: • SPSS: p(obtained).000<p(critical)=.001 • Statistically significant at the .001 or .1% level 9 Example: Interpretation of Unstandardized Regression Coefficients • GDP per capita variable: – Increase of $1000 in the GDP per capita increases the democracy score on a scale from 1 to 7 by .199 units keeping other variables constant • French colony variable: • The average former French colony has democracy score which is .885 units smaller compared to the average former British colony keeping other variables constant • Catholic country variable: – The average Catholic country has democracy score which is about 1unit higher compared to the average Protestant country keeping other variables constant • Other religion variable: – The average Other religion country has democracy score which is .747 units higher compared to the average Protestant country keeping other variables constant 10 Example: Interpretation • Standardized Regression Coefficient of GDP per capita variable=.563 – The absolute value much higher compared to other variables • GDP per capita variable has the biggest effect on the level of democracy – Effects of the colonial dummy variables and religious dummy variables are much smaller • Adjusted R square=.481 • GDP per capita, colonial dummy variables, and religious dummy variables explain about 48% of variation in the Freedom House democracy scale 11 Interpretation of Results • The first research hypothesis is supported by multiple regression analysis • The level of economic development has a positive and statistically significant effect on democracy • The second research hypothesis is partly supported by multiple regression analysis • The former British colonies have higher levels of democracy compared to former French colonies • The third research hypothesis is not supported by multiple regression analysis • Protestant countries do not have higher levels of democracy compared to other countries keeping other variables constant 12