Interpreting and Using Regression, Volume 29; Volume 1982Interpreting and Using Regression sets out the actual procedures researchers employ, places them in the framework of statistical theory, and shows how good research takes account both of statistical theory and real world demands. Achen builds a working philosophy of regression that goes well beyond the abstract, unrealistic treatment given in previous texts. |
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Contents
Editors Introduction | 5 |
Elementary Regression Theory and Social Science Practice | 12 |
Statistical Properties of Regression Estimates | 30 |
Sampling Distributions of Regression CoefIicients | 37 |
Choosing a Specification | 51 |
The Importance of a Variable | 68 |
Conclusion | 77 |
84 | |
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Common terms and phrases
additional Analysis o1 answer assumptions average bias causal strength coefficient estimates compute confidence intervals correlation cube law data analysis data set Democratic dependent discussion disturbances dummy variables effect explained factors favored forecast functional form Gauss-Markov Theorem Hampshire hypothesis impact independent variables influence interpretation jackknife large samples least squares less linear Manchester Union Leader Manchester vote mean meaningful measure Merrill Shanks minimize Cp newspaper newspaper's normality null null hypothesis number of observations percentage points percentage seats plausible point cloud political postulates Predicted Vote Difference primary elections Professor Achen question reasonable regres regression analysis regression coefficients regression equation regression model relationship result sampling errors scale scores sense set of observations significance testing simply sion slope social science applications social scientists social theory standard error standardized beta statistical methods statistically significant story per day theoretical tion true unbiased Union Leader example University o1 unmeasured variance Veblen's z scores