King, Gary
Designing social inquiry : scientific inference in qualitative research - New Jersey : Princeton University Press, 1994 - 247 p.
1 - The science in social science Introduction Two styles of research, ine logic of inference Science and complexity Major components of research design Improving research questions Improving theory Improving data quality Improving the use of existing data Themes of this volume 2 - Descriptive inference General knowledge and particular facts Inference: the scientific purpose of data collection Formal models of qualitative research A formal model of data collection Summarizing historical detail Descriptive inference Criteria for judging descriptive inferences 3 - Causality and casual inference Defining casuality Qualifying alternative definitions of casuality Assumptions required for estimating casual effects Criteria for judging causal inferences Rules for constructing causal theories 4 - Determining what to observe Indeterminate research designs The limits of random selection Selection bias Intentional selection of observations Concluding remarks 5 - Understanding what to avoid Measuring error Excluding relevant variables: bias Including irrelevant variables: inefficiency Endogeneity Assigning values of the explanatory variable Controlling the research situation Concluding remarks Increasing the number of observations Single-observation designs for casual inference How many observations are enough? Making many observations from few Concluding remarks
Ciencias Sociais
Pesquisa
Método de Pesquisa
Designing social inquiry : scientific inference in qualitative research - New Jersey : Princeton University Press, 1994 - 247 p.
1 - The science in social science Introduction Two styles of research, ine logic of inference Science and complexity Major components of research design Improving research questions Improving theory Improving data quality Improving the use of existing data Themes of this volume 2 - Descriptive inference General knowledge and particular facts Inference: the scientific purpose of data collection Formal models of qualitative research A formal model of data collection Summarizing historical detail Descriptive inference Criteria for judging descriptive inferences 3 - Causality and casual inference Defining casuality Qualifying alternative definitions of casuality Assumptions required for estimating casual effects Criteria for judging causal inferences Rules for constructing causal theories 4 - Determining what to observe Indeterminate research designs The limits of random selection Selection bias Intentional selection of observations Concluding remarks 5 - Understanding what to avoid Measuring error Excluding relevant variables: bias Including irrelevant variables: inefficiency Endogeneity Assigning values of the explanatory variable Controlling the research situation Concluding remarks Increasing the number of observations Single-observation designs for casual inference How many observations are enough? Making many observations from few Concluding remarks
Ciencias Sociais
Pesquisa
Método de Pesquisa
