The fundamentals of political science research
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| Sprache: | English |
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Cambridge Univ. Press
2009
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| 100 | 1 | |a Kellstedt, Paul M. |d 1968- |e Verfasser |0 (DE-588)140932119 |4 aut | |
| 245 | 1 | 0 | |a The fundamentals of political science research |c Paul M. Kellstedt ; Guy D. Whitten |
| 246 | 1 | 3 | |a Political science research |
| 250 | |a 1. publ. | ||
| 264 | 1 | |a New York [u.a.] |b Cambridge Univ. Press |c 2009 | |
| 300 | |a XVIII, 272 S. |b graph. Darst. |c 26 cm | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 500 | |a Includes bibliographical references (p. 261-263) and index | ||
| 650 | 4 | |a Politische Wissenschaft | |
| 650 | 4 | |a Political science |x Research | |
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Datensatz im Suchindex
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|---|---|
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| _version_ | 1823054459206369280 |
| adam_text | Contents
Figures
page
xiii
Tables
xv
Acknowledgments
xvii
The Scientific Study of Politics
..................1
Overview
1
1.1
Political Science}
1
1.2
Approaching Politics Scientifically: The Search for Causal
Explanations
3
1.3
Thinking about the World in Terms of Variables and Causal
Explanations
7
1.4
Models of Politics
14
1.5
Rules of the Road to Scientific Knowledge about Politics
15
1.5.1
Make Your Theories Causal
15
1.5.2
Don t Let Data Alone Drive Your Theories
16
1.5.3
Consider Only Empirical Evidence
17
1.5.4
Avoid Normative Statements
17
1.5.5
Pursue Both Generality and Parsimony
18
1.6
A Quick Look Ahead
18
Concepts Introduced in This Chapter
19
Exercises
20
The Art of Theory Building
................... 22
Overview
22
2.1
Good Theories Come from Good Theory-Building Strategies
22
2.2
Identifying Interesting Variation
23
2.2.1
Time-Series Example
24
2.2.2
Cross-Sectional Example
25
2.3
Learning to Use Your Knowledge
26
2.3.1
Moving from a Specific Event to More General
Theories
26
«11
viii
Contents
2.3.2
Know Local, Think Global: Can You Drop the
Proper Nouns?
27
2.4
Examine Previous Research
28
2.4.1
What Did the Previous Researchers Miss?
29
2.4.2
Can Their Theory Be Applied Elsewhere?
29
2.4.3
If We Believe Their Findings, Are There Further
Implications?
30
2.4.4
How Might This Theory Work at Different Levels of
Aggregation
(Місго-Ф^Масго)? ЗО
2.5
Think Formally about the Causes That Lead to Variation in
Your Dependent Variable
31
2.5.1
Utility and Expected Utility
32
2.5.2
The Puzzle of Turnout
34
2.6
Think about the Institutions: The Rules Usually Matter
36
2.6.1
Legislative Rules
36
2.6.2
The Rules Matter!
38
2.7
Extensions
39
2.8
How Do I Know If I Have a Good Theory?
40
2.8.1
Is Your Theory Causal?
40
2.8.2
Can You Test Your Theory on Data That You Have
Not Yet Observed?
41
2.8.3
How General Is Your Theory?
41
2.8.4
How Parsimonious Is Your Theory?
41
2.8.5
How New Is Your Theory?
41
2.8.6
How Nonobvious Is Your Theory?
42
2.9
Conclusion
42
Concepts Introduced in This Chapter
43
Exercises
43
Evaluating Causal Relationships
................45
Overview
45
3.1
Causality and Everyday Language
45
3.2
Four Hurdles along the Route to Establishing Causal
Relationships
48
3.2.1
Putting It All Together
-
Adding Up the Answers to
Our Four Questions
50
3.2.2
Identifying Causal Claims Is an Essential
Thinking Skill
50
3.2.3
What Are the Consequences of Failing to Control
for Other Possible Causes?
53
3.3
Why Is Studying Causality So Important? Three Examples
from Political Science
54
3.3.1
Life Satisfaction and Democratic Stability
54
3.3.2
School Choice and Student Achievement
55
3.3.3
Electoral Systems and the Number of Political Parties
57
ix Contents
3.4
Why Is Studying Causality So Important? Three Examples
from Everyday Life
61
3.4.1
Alcohol Consumption and Income
61
3.4.2
Treatment Choice and Breast Cancer Survival
62
3.4.3
Explicit Lyrics and Teen Sexual Behavior
63
3.5
Wrapping Up
65
Concepts Introduced in This Chapter
65
Exercises
65
Research Design
........................67
Overview
67
4.1
Comparison as the Key to Establishing Causal Relationships
67
4.2
Experimental Research Designs
68
4.2.1
Random Assignment versus Random Sampling
74
4.2.2
Are There Drawbacks to Experimental Research
Designs?
74
4.3
Observational Studies (in Two Flavors)
77
4.3.1
Datum, Data, Data Set
79
4.3.2
Cross-Sectional Observational Studies
81
4.3.3
Time-Series Observational Studies
82
4.3.4
The Major Difficulty with Observational Studies
83
4.4
Summary
83
Concepts Introduced in This Chapter
84
Exercises
84
Measurement
..........................86
Overview
86
5.1
Why Measurement Matters
86
5.2
Social Science Measurement: The Varying Challenges of
Quantifying Humanity
88
5.3
Problems in Measuring Concepts of Interest
91
5.3.1
Conceptual Clarity
91
5.3.2
Reliability
92
5.3.3
Measurement Bias and Reliability
93
5.3.4
Validity
94
5.3.5
The Relationship between Validity and Reliability
95
5.4
Controversy
1:
Measuring Democracy
96
5.5
Controversy
2:
Measuring Political Tolerance
99
5.6
Are There Consequences to Poor Measurement?
101
5.7
Conclusions
101
Concepts Introduced in This Chapter
102
Exercises
102
Descriptive Statistics and Graphs
...............104
Overview
104
6.1
Know Your Data
104
Contents
6.2
What Is the Variable s Measurement Metric?
105
6.2.1
Categorical Variables
106
6.2.2
Ordinal Variables
106
6.2.3
Continuous Variables
107
6.2.4
Variable Types and Statistical Analyses
108
6.3
Describing Categorical Variables
109
6.4
Describing Continuous Variables
110
6.4.1
Rank Statistics 111
6.4.2
Moments
114
6.5
Limitations
118
Concepts Introduced in This Chapter
118
Exercises
118
Statistical Inference
...................... 120
Overview
120
7.1
Populations and Samples
120
7.2
Learning about the Population from a Sample: The Central
Limit Theorem
122
7.2.1
The Normal Distribution
122
7.3
Example: Presidential Approval Ratings
128
7.3.1
What Kind of Sample Was That?
129
7.3.2
A Note on the Effects of Sample Size
130
7.4
A Look Ahead: Examining Relationships between Variables
131
Concepts Introduced in This Chapter
132
Exercises
132
Bivariate Hypothesis Testing
.................134
Overview
134
8.1
Bivariate Hypothesis Tests and Establishing Causal
Relationships
134
8.2
Choosing the Right Bivariate Hypothesis Test
135
8.3
All Roads Lead to
p
136
8.3.1
The Logic of /^Values
136
8.3.2
The Limitations of p-Values
137
8.3.3
From p-Values to Statistical Significance
138
8.3.4
The Null Hypothesis and p-Values
138
8.4
Three Bivariate Hypothesis Tests
139
8.4.1
Example
1:
Tabular Analysis
139
8.4.2
Example
2:
Difference of Means
145
8.4.3
Example
3:
Correlation Coefficient
150
8.5
Wrapping Up
155
Concepts Introduced in This Chapter
156
Exercises
157
Bivariate Regression Models
.................159
Overview
159
9.1
Two-Variable Regression
159
9.2
Fitting a Line: Population -Q- Sample
160
xi Contents
9.3
Which Line Fits Best? Estimating the Regression Line
162
9.4
Measuring Our Uncertainty about the OLS Regression Line
165
9.4.1
Goodness-of-Fit: Root Mean-Squared Error
167
9.4.2
Goodness-of-Fit:
Ќ
-Squared
Statistic
167
9.4.3
Is That a Good Goodness-of-Fit?
169
9.4.4
Uncertainty about Individual Components of the
Sample Regression Model
169
9.4.5
Confidence Intervals about Parameter Estimates
171
9.4.6
Hypothesis Testing: Overview
172
9.4.7
Two-Tailed Hypothesis Tests
173
9.4.8
The Relationship between Confidence Intervals and
Two-Tailed Hypothesis Tests
175
9.4.9
One-Tailed Hypothesis Tests
175
9.5
Assumptions, More Assumptions, and Minimal Mathematical
Requirements
177
9.5.1
Assumptions about the Population Stochastic
Component
177
9.5.2
Assumptions about Our Model Specification
180
9.5.3
Minimal Mathematical Requirements
181
9.5.4
How Can We Make All of These Assumptions?
181
Concepts Introduced in This Chapter
182
Exercises
182
Multiple Regression Models I: The Basics
...........183
Overview
183
10.1
Modeling Multivariate Reality
183
10.2
The Population Regression Function
184
10.3
From Two-Variable to Multiple Regression
184
10.4
What Happens When We Fail to Control for Z?
188
10.4.1
An Additional Minimal Mathematical Requirement
in Multiple Regression
192
10.5
Interpreting Multiple Regression
193
10.6
Which Effect Is Biggest ?
196
10.7
Statistical and Substantive Significance
198
10.8
Implications
199
Concepts Introduced in This Chapter
200
Exercises
200
Multiple Regression Models II: Crucial Extensions
......202
Overview
202
11.1
Extensions of OLS
202
11.2
Being Smart with Dummy Independent Variables in OLS
203
11.2.1
Using Dummy Variables to Test Hypotheses about a
Categorical Independent Variable with Only Two
Values
203
11.2.2
Using Dummy Variables to Test Hypotheses about a
Categorical Independent Variable with More Than
Two Values
207
xii Contents
11.3
Testing
Interactive
Hypotheses with Dummy
Variables 210
11.4
Dummy Dependent Variables
212
11.4.1
The Linear Probability Model
212
11.4.2
Binomial Logit and Binomial
Probit
215
11.4.3
Goodness-of-Fit with Dummy Dependent Variables
219
11.5
Outliers and Influential Cases in OLS
220
11.5.1
Identifying Influential Cases
221
11.5.2
Dealing with Influential Cases
224
11.6
Multicollinearity
225
11.6.1
How Does Multicollinearity Happen?
226
11.6.2
Detecting Multicollinearity
227
11.6.3
Multicollinearity: A Simulated Example
228
11.6.4
Multicollinearity: A Real-World Example
230
11.6.5
Multicollinearity: What Should I Do?
232
11.7
Being Careful with Time Series
233
11.7.1
Time-Series Notation
233
11.7.2
Memory and Lags in Time-Series Analysis
234
11.7.3
Trends and the Spurious Regression Problem
236
11.7.4
The Differenced Dependent Variable
239
11.7.5
The Lagged Dependent Variable
241
11.8
Wrapping Up
242
Concepts Introduced in This Chapter
243
Multiple Regression Models III: Applications
.........244
Overview
244
12.1
Why Controlling for
Z
Matters
244
12.2
Example
1:
The Economy and Presidential Popularity
245
12.3
Example
2:
Politics, Economics, and Public Support for
Democracy
248
12.4
Example
3:
Competing Theories of How Politics Affects
International Trade
251
12.5
Conclusions
253
Concepts Introduced in This Chapter
254
Exercises
254
Appendix A. Critical Values of
χ2
..................255
Appendix B. Critical Values of
t
...................256
Appendix C. The A Link Function for BNL Models
..........257
Appendix D. The
Φ
Link Function for
BNP
Models
..........259
Bibliography
261
Index
265
|
| any_adam_object | 1 |
| author | Kellstedt, Paul M. 1968- Whitten, Guy D. |
| author_GND | (DE-588)140932119 |
| author_facet | Kellstedt, Paul M. 1968- Whitten, Guy D. |
| author_role | aut aut |
| author_sort | Kellstedt, Paul M. 1968- |
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| building | Verbundindex |
| bvnumber | BV035679839 |
| callnumber-first | J - Political Science |
| callnumber-label | JA86 |
| callnumber-raw | JA86 |
| callnumber-search | JA86 |
| callnumber-sort | JA 286 |
| callnumber-subject | JA - Political Science |
| classification_rvk | MB 1000 MB 2300 |
| ctrlnum | (OCoLC)612088732 (DE-599)BVBBV035679839 |
| dewey-full | 320.072 |
| dewey-hundreds | 300 - Social sciences |
| dewey-ones | 320 - Political science (Politics and government) |
| dewey-raw | 320.072 |
| dewey-search | 320.072 |
| dewey-sort | 3320.072 |
| dewey-tens | 320 - Political science (Politics and government) |
| discipline | Politologie |
| edition | 1. publ. |
| format | Book |
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| id | DE-604.BV035679839 |
| illustrated | Illustrated |
| indexdate | 2025-02-03T17:28:01Z |
| institution | BVB |
| isbn | 9780521875172 9780521697880 |
| language | English |
| lccn | 2008035250 |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-017734121 |
| oclc_num | 612088732 |
| open_access_boolean | |
| owner | DE-473 DE-BY-UBG DE-19 DE-BY-UBM DE-355 DE-BY-UBR DE-188 |
| owner_facet | DE-473 DE-BY-UBG DE-19 DE-BY-UBM DE-355 DE-BY-UBR DE-188 |
| physical | XVIII, 272 S. graph. Darst. 26 cm |
| publishDate | 2009 |
| publishDateSearch | 2009 |
| publishDateSort | 2009 |
| publisher | Cambridge Univ. Press |
| record_format | marc |
| spellingShingle | Kellstedt, Paul M. 1968- Whitten, Guy D. The fundamentals of political science research Politische Wissenschaft Political science Research Methode (DE-588)4038971-6 gnd Forschungsmethode (DE-588)4155046-8 gnd Theoriebildung (DE-588)4185105-5 gnd Methodologie (DE-588)4139716-2 gnd Politische Wissenschaft (DE-588)4076229-4 gnd Forschungsprozess (DE-588)4155054-7 gnd Empirische Sozialforschung (DE-588)4014606-6 gnd |
| subject_GND | (DE-588)4038971-6 (DE-588)4155046-8 (DE-588)4185105-5 (DE-588)4139716-2 (DE-588)4076229-4 (DE-588)4155054-7 (DE-588)4014606-6 |
| title | The fundamentals of political science research |
| title_alt | Political science research |
| title_auth | The fundamentals of political science research |
| title_exact_search | The fundamentals of political science research |
| title_full | The fundamentals of political science research Paul M. Kellstedt ; Guy D. Whitten |
| title_fullStr | The fundamentals of political science research Paul M. Kellstedt ; Guy D. Whitten |
| title_full_unstemmed | The fundamentals of political science research Paul M. Kellstedt ; Guy D. Whitten |
| title_short | The fundamentals of political science research |
| title_sort | the fundamentals of political science research |
| topic | Politische Wissenschaft Political science Research Methode (DE-588)4038971-6 gnd Forschungsmethode (DE-588)4155046-8 gnd Theoriebildung (DE-588)4185105-5 gnd Methodologie (DE-588)4139716-2 gnd Politische Wissenschaft (DE-588)4076229-4 gnd Forschungsprozess (DE-588)4155054-7 gnd Empirische Sozialforschung (DE-588)4014606-6 gnd |
| topic_facet | Politische Wissenschaft Political science Research Methode Forschungsmethode Theoriebildung Methodologie Forschungsprozess Empirische Sozialforschung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017734121&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT kellstedtpaulm thefundamentalsofpoliticalscienceresearch AT whittenguyd thefundamentalsofpoliticalscienceresearch AT kellstedtpaulm politicalscienceresearch AT whittenguyd politicalscienceresearch |