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1. ProQuest statistical abstract of the United States [2013  ]
 Lanham, Maryland : Bernan, 2012
 Description
 Journal/Periodical — volumes : maps ; 29 cm
 Database topics
 American History; Communication and Journalism; Government Information: United States; Statistical and Numeric Data
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HA202 .A483 2018  Inlibrary use 
 Welkowitz, Joan.
 7th ed.  Hoboken, N.J. : Wiley, c2012.
 Description
 Book — xxiii, 545 p. : ill. ; 25 cm.
 Summary

 Preface xv Acknowledgments xix Glossary of Symbols xxi Part I Descriptive Statistics
 1
 Chapter 1 Introduction
 3 Why Study Statistics?
 4 Descriptive and Inferential Statistics
 5 Populations, Samples, Parameters, and Statistics
 6 Measurement Scales
 7 Independent and Dependent Variables
 10 Summation Notation
 12 Ihno s Study
 16 Summary
 18 Exercises
 19 Thought Questions
 23 Computer Exercises
 23 Bridge to SPSS
 24
 Chapter 2 Frequency Distributions and Graphs
 26 The Purpose of Descriptive Statistics
 27 Regular Frequency Distributions
 28 Cumulative Frequency Distributions
 30 Grouped Frequency Distributions
 31 Real and Apparent Limits
 33 Interpreting a Raw Score
 34 Definition of Percentile Rank and Percentile
 34 Computational Procedures
 35 Deciles, Quartiles, and the Median
 38 Graphic Representations
 39 Shapes of Frequency Distributions
 43 Summary
 45 Exercises
 47 Thought Questions
 49 Computer Exercises
 49 Bridge to SPSS
 50
 Chapter 3 Measures of Central Tendency and Variability
 53 Introduction
 54 The Mode
 56 The Median
 56 The Mean
 58 The Concept of Variability
 62 The Range
 65 The Standard Deviation and Variance
 66 Summary
 73 Exercises
 75 Thought Questions
 76 Computer Exercises
 77 Bridge to SPSS
 78
 Chapter 4 Standardized Scores and the Normal Distribution
 81 Interpreting a Raw Score Revisited
 82 Rules for Changing and
 84 Standard Scores (z Scores)
 85 T Scores, SAT Scores, and IQ Scores
 88 The Normal Distribution
 90 Table of the Standard Normal Distribution
 93 Illustrative Examples
 95 Summary
 101 Exercises
 103 Thought Questions
 105 Computer Exercises
 106 Bridge to SPSS
 106 Part II Basic Inferential Statistics
 109
 Chapter 5 Introduction to Statistical Inference
 111 Introduction
 113 The Goals of Inferential Statistics
 114 Sampling Distributions
 114 The Standard Error of the Mean
 119 The z Score for Sample Means
 122 Null Hypothesis Testing
 124 Assumptions Required by the Statistical Test for the Mean of a Single Population
 132 Summary
 133 Exercises
 135 Thought Questions
 137 Computer Exercises
 138 Bridge to SPSS
 138 Appendix: The Null Hypothesis Testing Controversy
 139
 Chapter 6 The OneSample t Test and Interval Estimation
 142 Introduction
 143 The Statistical Test for the Mean of a Single Population When Is Not Known: The t Distributions
 144 Interval Estimation
 148 The Standard Error of a Proportion
 152 Summary
 155 Exercises
 156 Thought Questions
 157 Computer Exercises
 158 Bridge to SPSS
 158
 Chapter 7 Testing Hypotheses About the Difference Between the Means of Two Populations
 160 The Standard Error of the Difference
 162 Estimating the Standard Error of the Difference
 166 The t Test for Two Sample Means
 167 Confidence Intervals for
 1
 2
 172 The Assumptions Underlying the Proper Use of the t Test for Two Sample Means
 175 Measuring the Size of an Effect
 176 The t Test for Matched Samples
 178 Summary
 185 Exercises
 187 Thought Questions
 190 Computer Exercises
 191 Bridge to SPSS
 191
 Chapter 8 Nonparametric Tests for the Difference Between Two Means
 194 Introduction
 195 The Difference Between the Locations of Two Independent Samples: The RankSum Test
 199 The Difference Between the Locations of Two Matched Samples: The Wilcoxon Test
 205 Summary
 210 Exercises
 212 Thought Questions
 215 Computer Exercises
 216 Bridge to SPSS
 216
 Chapter 9 Linear Correlation
 218 Introduction
 219 Describing the Linear Relationship Between Two Variables
 222 Interpreting the Magnitude of a Pearson r
 229 When Is It Important That Pearson s r Be Large?
 234 Testing the Significance of the Correlation Coefficient
 236 The Relationship Between Two Ranked Variables: The Spearman RankOrder Correlation Coefficient
 239 Summary
 242 Exercises
 244 Thought Questions
 247 Computer Exercises
 248 Bridge to SPSS
 248 Appendix: Equivalence of the Various Formulas for r
 251
 Chapter 10 Prediction and Linear Regression
 253 Introduction
 254 Using Linear Regression to Make Predictions
 254 Measuring Prediction Error: The Standard Error of Estimate
 263 The Connection Between Correlation and the t Test
 265 Estimating the Proportion of Variance Accounted for in the Population
 271 Summary
 273 Exercises
 275 Thought Questions
 277 Computer Exercises
 277 Bridge to SPSS
 278
 Chapter 11 Introduction to Power Analysis
 281 Introduction
 282 Concepts of Power Analysis
 283 The Significance Test of the Mean of a Single Population
 285 The Significance Test of the Proportion of a Single Population
 290 The Significance Test of a Pearson r
 292 Testing the Difference Between Independent Means
 293 Testing the Difference Between the Means of Two Matched Populations
 297 Choosing a Value for d for a Power Analysis Involving Independent Means
 299 Using Power Analysis Concepts to Interpret the Results of Null Hypothesis Tests
 301 Summary
 304 Exercises
 306 Thought Questions
 308 Computer Exercises
 309 Bridge to SPSS
 310 Part III Analysis of Variance Methods
 313
 Chapter 12 OneWay Analysis of Variance
 315 Introduction
 317 The General Logic of ANOVA
 318 Computational Procedures
 321 Testing the F Ratio for Statistical Significance
 326 Calculating the OneWay ANOVA From Means and Standard Deviations
 328 Comparing the OneWay ANOVA With the t Test
 329 A Simplified ANOVA Formula for Equal Sample Sizes
 330 Effect Size for the OneWay ANOVA
 331 Some Comments on the Use of ANOVA
 333 A Nonparametric Alternative to the OneWay ANOVA: The KruskalWallis H Test
 336 Summary
 339 Exercises
 343 Thought Questions
 346 Computer Exercises
 346 Bridge to SPSS
 346 Appendix: Proof That the Total Sum of Squares Is Equal to the Sum of the BetweenGroup and the WithinGroup Sum of Squares
 348
 Chapter 13 Multiple Comparisons
 349 Introduction
 350 Fisher s Protected t Tests and the Least Significant Difference (LSD)
 351 Tukey s Honestly Significant Difference (HSD)
 355 Other Multiple Comparison Procedures
 360 Planned and Complex Comparisons
 362 Nonparametric Multiple Comparisons: The Protected RankSum Test
 365 Summary
 366 Exercises
 368 Thought Questions
 369 Computer Exercises
 370 Bridge to SPSS
 370
 Chapter 14 Introduction to Factorial Design: TwoWay Analysis of Variance
 372 Introduction
 373 Computational Procedures
 374 The Meaning of Interaction
 384 Following Up a Significant Interaction
 387 Measuring Effect Size in a Factorial ANOVA
 390 Summary
 392 Exercises
 395 Thought Questions
 398 Computer Exercises
 399 Bridge to SPSS
 399
 Chapter 15 RepeatedMeasures ANOVA
 402 Introduction
 403 Calculating the OneWay RM ANOVA
 403 Rationale for the RM ANOVA Error Term
 408 Assumptions and Other Considerations Involving the RM ANOVA
 408 The RM Versus RB Design: An Introduction to the Issues of Experimental Design
 411 The TwoWay Mixed Design
 415 Summary
 423 Exercises
 428 Thought Questions
 430 Computer Exercises
 430 Bridge to SPSS
 431 Part IV Nonparametric Statistics for Categorical Data
 435
 Chapter 16 Probability of Discrete Events and the Binomial Distribution
 437 Introduction
 438 Probability
 439 The Binomial Distribution
 442 The Sign Test for Matched Samples
 448 Summary
 450 Exercises
 451 Thought Questions
 453 Computer Exercises
 453 Bridge to SPSS
 454
 Chapter 17 ChiSquare Tests
 457 Chi Square and the Goodness of Fit: OneVariable Problems
 458 Chi Square as a Test of Independence: TwoVariable Problems
 464 Measures of Strength of Association in TwoVariable Tables
 470 Summary
 472 Exercises
 474 Thought Questions
 476 Computer Exercises
 477 Bridge to SPSS
 478
 Appendix 481 Statistical Tables
 483 Answers to OddNumbered Exercises
 499 Data From Ihno s Experiment
 511 Glossary of Terms
 515 References
 525 Index 527.
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3. Differential item functioning [2009]
 Osterlind, Steven J.
 2nd ed.  Thousand Oaks, Calif. : SAGE, c2009.
 Description
 Book — x, 87 p. : ill. ; 22 cm.
 Summary

 About the Authors Series Editor's Introduction
 1. Introduction
 2. Description of DIF
 3. Statistical Facets of DIF
 4. Important Considerations
 5. History of Test Bias and DIF
 6. QuickButIncomplete Methods
 7. MantelHaenszel Procedure
 8. Nonparametic Methods
 9. IRTBased Methods
 10. Logistic Regression
 11. Specialized DIF Procedures
 12. Future Directions Conclusion References Author Index Subject Index.
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4. Fixed effects regression models [2009]
 Allison, Paul David.
 Los Angeles, Calif. : SAGE, c2009.
 Description
 Book — x, 123 p. : ill. ; 22 cm.
 Summary

 About the Author Series Editor's Introduction
 1. Introduction
 2. Linear Fixed Effects Models: Basics
 3. Fixed Effects Logistic Models
 4. Fixed Effects Models for Count Data
 5. Fixed Effects Models for Events History Data
 6. Structural Equation Models With Fixed Effects
 Appendix 1
 Appendix 2 References Author Index Subject Index.
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5. Survey methodology [2009]
 2nd ed.  Hoboken, N.J. : Wiley, ©2009.
 Description
 Book — xxi, 461 pages : ill., maps ; 26 cm.
 Summary

 PREFACE TO THE FIRST EDITION xv PREFACE TO THE SECOND EDITION xix ACKNOWLEDGEMENTS xxi
 CHAPTER 1. AN INTRODUCTION TO SURVEY METHODOLOGY 1.1 Introduction
 2 1.2 A Brief History of Survey Research
 3 1.3 Some Examples of Ongoing Surveys
 7 1.4 What is Survey Methodology?
 30 1.5 The Challenge of Survey Methodology
 32 1.6 About this Book
 34
 CHAPTER 2. INFERENCE AND ERROR IN SURVEYS 2.1 Introduction
 39 2.2 The Lifecycle of a Survey From a Design Perspective
 41 2.3 The Lifecycle of a Survey from A Quality Perspective
 49 2.4 Putting It All Together
 60 2.5 Error Notions in Different Kinds of Statistics
 61 2.6 Nonstatistical Notions of Survey Quality
 62 2.7 Summary
 63
 CHAPTER 3. TARGET POPULATIONS, SAMPLING FRAMES, AND COVERAGE ERROR 3.1 Introduction
 69 3.2 Populations and Frames
 69 3.3 Coverage Properties of Sampling Frames
 72 3.4 Alternative Frames for the Target Population of Households or Persons
 81 3.5 Frame Issues for Other Common Target Populations
 84 3.6 Coverage Error
 87 3.7 Reducing Undercoverage
 88 3.8 Summary
 94
 CHAPTER 4. SAMPLE DESIGN AND SAMPLING ERROR 4.1 Introduction
 97 4.2 Samples and Estimates
 99 4.3 Simple Random Sampling
 103 4.4 Cluster Sampling
 106 4.5 Stratification and Stratified Sampling
 113 4.6 Systematic Selection
 123 4.7 Complications in Practice
 125 4.8 Sampling US Telephone Households
 133 4.9 Selecting Persons Within Households
 136 4.10 Summary
 138
 CHAPTER 5. METHODS OF DATA COLLECTION 5.1 Alternative Methods of Data Collection
 150 5.2 Choosing the Appropriate Method
 159 5.3 Effects of Different Data Collection Methods on Survey Errors
 160 5.4 Using Multiple Modes of Data Collection
 175 5.5 Summary
 177
 CHAPTER 6. NONRESPONSE IN SAMPLE SURVEYS 6.1 Introduction
 183 6.2 Response Rates
 183 6.3 Impact of Nonresponse on the Quality of Survey Estimates
 189 6.4 Thinking Causally About Survey Nonresponse Error
 191 6.5 Dissecting the Nonresponse Phenomenon
 192 6.6 Design Features to Reduce Unit Nonresponse
 201 6.7 Item Nonresponse
 208 6.8 Are Nonresponse Propensities Related to Other Error Sources?
 210 6.9 Summary
 210
 CHAPTER 7. QUESTIONS AND ANSWERS IN SURVEYS 7.1 Alternatives Methods of Survey Measurement
 217 7.2 Cognitive Processes in Answering Questions
 218 7.3 Problems in Answering Survey Questions
 225 7.4 Guidelines for Writing Good Questions
 242 7.5 Summary
 252
 CHAPTER 8. EVALUATING SURVEY QUESTIONS 8.1 Introduction
 259 8.2 Expert Reviews
 260 8.3 Focus Groups
 261 8.4 Cognitive Interviews
 263 8.5 Field Pretests and Behavior Coding
 265 8.6 Randomized or SplitBallot Experiments
 267 8.7 Applying Question Standards
 268 8.8 Summary of Question Evaluation Tools
 269 8.9 Linking Concepts of Measurement Quality to Statistical Estimates
 274 8.10 Summary
 286
 CHAPTER 9. SURVEY INTERVIEWING 9.1 The Role of the Interviewer
 291 9.2 Interviewer Bias
 292 9.3 Interviewer Variance
 295 9.4 Strategies for Reducing Interviewer Bias
 300 9.5 Strategies for Reducing InterviewerRelated Variance
 302 9.6 The Controversy About Standardized Interviewing
 312 9.7 Interviewer Management
 315 9.8 Validating the Work of Interviewers
 319 9.9 The Use of Recorded Voices (and Faces) in Data Collection
 322 9.10 Summary
 323
 CHAPTER 10. POSTCOLLECTION PROCESSING OF SURVEY DATA 10.1 Introduction
 329 10.2 Coding
 331 10.3 Entering Numeric Data into Files
 344 10.4 Editing
 345 10.5 Weighting
 347 10.6 Imputation for Itemmissing data
 354 10.7 Sampling Variance Estimation for Complex Samples
 359 10.8 Survey Data Documentation and Metadata
 363 10.9 Summary
 365
 CHAPTER 11. PRINCIPLES AND PRACTICES RELATED TO ETHICAL RESEARCH 11.1 Introduction
 371 11.2 Standards for the Conduct of Research
 371 11.3 Standards for Dealing with Clients
 374 11.4 Standards for Dealing with the Public
 375 11.5 Standards for Dealing with Respondents
 376 11.6 Emerging Ethical Issues
 384 11.7 Research About Ethical Issues in Surveys
 384 11.8 Administrative and Technical Procedures for SafeGuarding Confidentiality
 392 11.9 Summary and Conclusions
 398 Keywords For More InDepth Reading Exercises
 CHAPTER 12. FAQS ABOUT SURVEY METHODOLOGY 12.1 Introduction
 405 12.2 The Questions and Their Answers
 405 REFERENCES
 421 INDEX 451.
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 Healey, Joseph F., 1945
 Belmont, CA : Thomson/Wadsworth, c2007.
 Description
 Book — xx, 406 p. : ill. ; 24 cm.
 Summary

Known for his exceptional and studentfriendly writing style, Joseph Healey's new book provides the essentials of statistics, makes no assumptions about the students' knowledge of math, and is very applied in its approach. The book's primary emphasis is on developing the student's skills to become 'statistically literate, ' with computational competence and the ability to read social science literature with greater comprehension.
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HA29 .H39 2007  Unknown 
 Millennial ed.  New York : Cambridge University Press, c2006.
 Description
 Book — 5 v. : ill., maps ; 29 cm.
 Database topics
 Statistical and Numeric Data
 Summary

 Search and navigate across data covering the following topics:
 1. Population: Population Characteristics Vital Statistics Internal Migration International Migration Family and Household Composition Cohorts American Indians
 2. Work and Welfare: Labor Slavery Education Health Economic Inequality and Poverty Social Insurance and Public Assistance Nonprofit, Voluntary, and Religious Entities
 3. Economic Structure and Performance: National Income and Product Business Fluctuations and Cycles Prices Consume Expenditures Saving, Capital, and Wealth Geography and the Environment Science, Technology, and Productivity Business Organization Financial Markets and Institutions
 4. Economic Sectors: Agriculture, Natural Resource Industries Construction, Housing, and Mortgages Manufacturing Distribution Transportation Communications Services and Utilities
 5. Governance and International Relations: Government Finance and Employment Elections and Politics Crime, Law Enforcement, and Justice National Defense, Wars, Armed Forces, and Veterans International Trade and Exchange Rates Outlying Areas Colonial Statistics Confederate States of America.
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 Dunteman, George H. (George Henry), 1935
 Thousand Oaks, Calif. : Sage Publications, c2006.
 Description
 Book — x, 72 p. : ill. ; 22 cm.
 Summary

 List of Figures and Tables Series Editor's Introduction Acknowledgments
 1. Generalized Linear Models
 2. Some Basic Modeling Concepts Categorical Independent Variables Essential Components of Regression Modeling
 3. Classical Multiple Regression Model Assumptions and Modeling Approach Results of Regression Analysis Multiple Correlation Testing Hypotheses
 4. Fundamentals of Generalized Linear Modeling Exponential Family of Distributions Classical Normal Regression Logistic Regression Poisson Regression Proportional Hazards Survival Model
 5. Maximum Likelihood Estimation
 6. Deviance and Goodness of Fit Using Deviances to Test Statistical Hypotheses Goodness of Fit Assessing Goodness of Fit by Residual Analysis
 7. Logistic Regression Example of Logistic Regression
 8. Poisson Regression Example of Poisson Regression Model
 9. Survival Analysis Survival Time Distributions Exponential Survival Model Example of Exponential Survival Model Conclusions Appendix References Index About the Authors.
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HA31.3 .D86 2006  Unknown 
 Welkowitz, Joan.
 6th ed.  Hoboken, N.J. : Wiley, c2006.
 Description
 Book — xxiii, 515 p. : ill. ; 25 cm.
 Summary

 Preface. Acknowledgments. Glossary of Symbols. PART I: DESCRIPTIVE STATISTICS.
 Chapter 1. Introduction.
 Chapter 2. Frequency Distributions and Graphs.
 Chapter 3. Transformed Scores I: Percentiles.
 Chapter 4. Measures of Central Tendency.
 Chapter 5. Measures of Variability.
 Chapter 6. Additional Techniques for Describing Batches of Data.
 Chapter 7. Transformed Scores II: z and T Scores.
 Chapter 8. The Normal Distribution. PART II: BASIC INFERENTIAL STASTICS.
 Chapter 9. Introduction to Statistical Inference.
 Chapter 10. The OneSample t Test and Interval Estimation.
 Chapter 11. Testing Hypotheses about the Difference between the Means of Two Populations.
 Chapter 12. Linear Correlation and Prediction.
 Chapter 13. The Connection between Correlation and the t Test.
 Chapter 14. Introduction to Power Analysis. PART III: Analysis of Variance Methods.
 Chapter 15. OneWay Analysis of Variance.
 Chapter 16. Multiple Comparisons.
 Chapter 17. Introduction to Factorial Design: TwoWay Analysis of Variance.
 Chapter 18. RepeatedMeasures ANOVA. PART IV: NONPARAMETRIC STATISTICS.
 Chapter 19. Introduction to Probability and Nonparametric Methods.
 Chapter 20. Chi Square Tests.
 Chapter 21. Tests for Ordinal Data. Appendix. Glossary of Terms. References. Index.
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HA29 .W445 2006  Unknown 
 O'Connell, Ann A.
 Thousand Oaks, Calif. : SAGE Publications, c2006.
 Description
 Book — xi, 107 p. ; 22 cm.
 Summary

 List of Tables and Figures Series Editor's Introduction Acknowledgments
 1. Introduction Purpose of This Book Software and Syntax Organization of the Chapters
 2. Context: Early Childhood Longitudinal Study Overview of the Early Childhood Longitudinal Study Practical Relevance of Ordinal Outcomes Variables in the Models
 3. Background: Logistic Regression Overview of Logistic Regression Assessing Model Fit Interpreting the Model Measures of Association EXAMPLE 3.1: Logistic Regression Comparing Results Across Statistical Programs
 4. The Cumulative (Proportional) Odds Model for Ordinal Outcomes Overview of the Cumulative Odds Model EXAMPLE 4.1: Cumulative Odds Model With a Single Explanatory Variable EXAMPLE 4.2: FullModel Analysis of Cumulative Odds Assumption of Proportional Odds and Linearity in the Logit Alternatives to the Cumulative Odds Model EXAMPLE 4.3: Partial Proportional Odds
 5. The Continuation Ratio Model Overview of the Continuation Ratio Model Link Functions Probabilities of Interest Directionality of Responses and Formation of the Continuation Ratios EXAMPLE 5.1: Continuation Ratio Model With Logit Link and Restructuring the Data EXAMPLE 5.2: Continuation Ratio Model With Complementary LogLog Link Choice of Link and Equivalence of Two ClogLog Models Choice of Approach for Continuation Ratio Models EXAMPLE 5.3: FullModel Continuation Ratio Analyses for the ECLSK Data
 6. The Adjacent Categories Model Overview of the Adjacent Categories Model EXAMPLE 6.1: GenderOnly Model EXAMPLE 6.2: Adjacent Categories Model With Two Explanatory Variables EXAMPLE 6.3: Full Adjacent Categories Model Analysis
 7. Conclusion Considerations for Further Study Notes Appendix A:
 Chapter 3 Appendix B:
 Chapter 4 Appendix C:
 Chapter 5 Appendix D:
 Chapter 6 References Index About the Author.
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11. Data analysis using stata [2005]
 Kohler, Ulrich, Dr. phil.
 College Station, TX : Stata Press, c2005.
 Description
 Book — xviii, 378 p. : ill. ; 24 cm.
 Summary

 PrefaceABOUT THE BOOKStructureUsing This book: Materials and hintsTeaching with this manual"THE FIRST TIME"Starting StataSetting up your screenYour first analysisDofilesExiting StataWORKING WITH DOFILESFrom interactive work to working with a dofileDesigning dofilesOrganizing your workSummaryTHE GRAMMAR OF STATAThe elements of Stata commandsRepeating similar commandsWeightsSOME GENERAL COMMENTS ON THE STATISTICAL COMMANDSCREATING AND CHANGING VARIABLESThe commands generate and replaceSpecialized recoding commandsAdditional tools for recording dataCommands for dealing with missing valuesLabelsStorage types, or, the ghost in the machineCREATING AND CHANGING GRAPHSA primer on graph syntaxGraph typesGraph elementsMultiple graphsSaving and printing graphsDESCRIBING AND COMPARING DISTRIBUTIONSCategories: Few or many?Variables with few categoriesVariables with many categoriesSummaryINTRODUCTION TO LINEAR REGRESSIONSimple linear regressionMultiple regressionRegression diagnosticsModel extensionsMore on standard errorsAdvanced techniquesSummaryREGRESSION MODELS FOR CATEGORICAL DEPENDENT VARIABLESThe linear probability modelBasic conceptsLogistic regression with StataLogistic regression diagnosticsLikelihoodratio testRefined modelsAdvanced techniquesSummaryREADING AND WRITING DATAThe goal: The data matrixImporting machinereadable dataInputting dataCombining dataSaving and exporting dataHandling big datasetsSummaryDOFILES FOR ADVANCED USERS AND USERWRITTEN PROGRAMSTwo examples of usageFour programming toolsUserwritten Stata commandsSummaryAROUND STATAResources and informationTaking care of StataAdditional proceduresReferencesAuthor IndexSubject Index.
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 Vogt, W. Paul.
 3rd ed.  Thousand Oaks, Calif. : Sage Publications, c2005.
 Description
 Book — xix, 353 p. : ill. ; 24 cm.
 Summary

 List of Figures List of Tables Preface to the Third Edition Preface to the Second Edition Preface to the First Edition Introduction How to Use This Dictionary A B C D E F G H I J K L M N O P Q R S T U V W X Y Z Suggestions for Further Reading About the Author.
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 Field, Andy P.
 2nd ed.  London ; Thousand Oaks : SAGE, 2005.
 Description
 Book — xxxiv, 779 p. : ill. ; 24 cm.
 Summary

 EVERYTHING YOU WANTED TO KNOW ABOUT STATISTICS (WELL, SORT OF) Building Statistical Models Populations and Samples Simple Statistical Models Frequency Distributions Is My Sample Representative of the Population? Linear Models How Can We Tell If Our Model Represents the Real World? THE SPSS ENVIRONMENT Versions of SPSS Getting Started The Data Editor The Output Viewer The Syntax Window Saving Files Retrieving a File EXPLORING DATA Parametric Data Graphing and Screening Data Exploring Groups of Data Testing Whether a Distribution is Normal Testing for Homogeneity of Variance Graphing Means CORRELATION How Do We Measure Relationships? Data Entry for Correlation Analysis Using SPSS Graphing Relationships The Scatterplot Bivariate Correlation Partial Correlation How To Report Correlation Coefficients REGRESSION An Introduction to Regression Doing Simple Regression on SPSS Interpreting a Simple Regression Multiple Regression The Basics How Accurate Is My Regression Model? How To Do Multiple Regression Using SPSS Interpreting Multiple Regression How To Report Multiple Regression Categorical Predictors and Multiple Regression LOGISTIC REGRESSION Background to Logistic Regression What Are the Principles behind Logistic Regression? Running the Analysis A Research Example Interpreting Logistic Regression How To Report Logistic Regression Another Example Testing for Multicollinearity Things That Can Go Wrong COMPARING TWO MEANS Revision of Experimental Research Inputting Data and Displaying Means with Error Bar Charts Testing Differences between Means The tTest The Dependent tTest The Independent tTest Between Groups or Repeated Measures? The tTest as a General Linear Model What If Our Data Are Not Normally Distributed? COMPARING SEVERAL MEANS: ANOVA (GLM 1) The Theory behind ANOVA Running OneWay ANOVA on SPSS Output from OneWay ANOVA Calculating the Effect Size Reporting Results from OneWay Independent ANOVA Violations of Assumptions in OneWay Independent ANOVA ANALYSIS OF COVARIANCE, ANCOVA (GLM 2) What Is ANCOVA? Conducting ANCOVA on SPSS Interpreting the Output from ANCOVA ANCOVA Run as a Multiple Regression Additional Assumptions in ANCOVA Calculating the Effect Size Reporting Results FACTORIAL ANOVA (GLM 3) Theory of Factorial ANOVA (Between Groups) Factorial ANOVA Using SPSS Output from Factorial ANOVA Interpreting Interaction Graphs Calculating Effect Sizes Reporting the Results of TwoWay ANOVA Factorial ANOVA as Regression REPEATEDMEASURES DESIGNS (GLM 4) Introduction to RepeatedMeasures Designs Theory of OneWay RepeatedMeasures ANOVA OneWay RepeatedMeasures ANOVA Using SPSS Output for OneWay RepeatedMeasures ANOVA Effect Sizes for RepeatedMeasures ANOVA Reporting OneWay RepeatedMeasures ANOVA RepeatedMeasures with Several Independent Variables Output for Factorial RepeatedMeasures ANOVA Effect Sizes for Factorial RepeatedMeasures ANOVA Reporting the Results from Factorial RepeatedMeasures ANOVA MIXED DESIGN ANOVA (GLM 5) Mixed ANOVA on SPSS Output for Mixed Factorial ANOVA Main Analysis Calculating Effect Sizes Reporting the Results of Mixed ANOVA NONPARAMETRIC TESTS Comparing Two Independent Conditions The Wilcoxon RankSum Test and MannWhitney Test Comparing Two Related Conditions The Wilcoxon SignedRank Test Differences between Several Independent Groups The KruskalWallis Test Differences between Several Related Groups Friedman's ANOVA MULTIVARIATE ANALYSIS OF VARIANCE (MANOVA) Introduction Similarities and Differences to ANOVA Theory of MANOVA Assumptions of MANOVA MANOVA on SPSS Output from MANOVA Following Up MANOVA with Discriminant Analysis Output from the Discriminant Analysis EXPLORATORY FACTOR ANALYSIS Factors Discovering Factors Research Example Running the Analysis Interpreting Output from SPSS Reliability Analysis CATEGORICAL DATA Theory of Analyzing Categorical Data Assumptions of the ChiSquare Test Doing ChiSquare on SPSS Several Categorical Variables Log Linear Analysis Assumptions in Loglinear Analysis Loglinear Analysis Using SPSS Output from Loglinear Analysis Following Up Loglinear Analysis Effect Sizes in Loglinear Analysis Reporting the Results of Loglinear Analysis.
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 Keppel, Geoffrey.
 4th ed.  Upper Saddle River, N.J. : Pearson Prentice Hall, c2004.
 Description
 Book — xii, 611 p. : ill. ; 25 cm.
 Summary

 I. INTRODUCTION.
 1. Experimental Design. II. SINGLE FACTOR EXPERIMENTS.
 2. Sources of Variability and Sums of Squares.
 3. Variance Estimates and F Ratio.
 4. Analytical Comparisons Among Means.
 5. Analysis of Trend.
 6. Simultaneous Comparisons.
 7. The Linear Model and Its Assumptions.
 8. Effect Size and Power.
 9. Using Statistical Software. III. FACTORIAL EXPERIMENTS WITH TWO FACTORS.
 10. Introduction to the Factorial Design.
 11. The Principal TwoFactor Effects.
 12. Main Effects and Simple Effects.
 13. The Analysis of Interaction Components. IV. NONORTHOGONALITY AND THE GENERAL LINEAR MODEL.
 14. General Linear Model.
 15. The Analysis of Covariance. V. WITHINSUBJECT DESIGNS.
 16. The SingleFactor WithinSubject Design.
 17. Further WithinSubject Topics.
 18. The TwoFactor WithinSubject Design.
 19. The Mixed Design: Overall Analysis.
 20. The Mixed Design: Analytical Analyses. VI. HIGHER FACTORIAL DESIGNS AND OTHER EXTENSIONS.
 21. The Overall ThreeFactor Design.
 22. The ThreeWay Analytical Analysis.
 23. WithinSubject and Mixed Designs.
 24. Random Factors and Generalization.
 25. Nested Factors.
 26. HigherOrder Designs. Appendix A: Statistical Tables.
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15. Interaction effects in multiple regression [2003]
 Jaccard, James.
 2nd ed.  Thousand Oaks, Calif. : Sage Publications, c2003.
 Description
 Book — vii, 92 p. : ill. ; 22 cm.
 Summary

 Series Editor's Introduction Preface
 Chapter 1: Introduction The Concept of Interaction Simple Effects and Interaction Contrasts Simple Effects Interaction Contrasts A Review of Multiple Regression The Linear Model Hierarchical Regression Categorical Predictors and Dummy Variables Predicted Values in Multiple Regression Transformations of the Predictor Variables Overview of Book
 Chapter 2: TwoWay Interactions Regression Models with Product Terms Two Continuous Predictors The Traditional Regression Strategy The Form of the Interaction Interpreting the Regression Coefficients for the Product Term Interpreting the Regression Coefficients for the Component Terms Significance Tests and Confidence Intervals Multicollinearity Strength of the Interaction Effect A Numerical Example Graphical Presentation A Qualitative Predictor and a Continuous Predictor A Qualitative Moderator Variable A Continuous Moderator Variable More Than Two Groups for the Qualitative Variable Form of the Interaction Summary
 Chapter 3: ThreeWay Interactions Three Continuous Predictors Qualitative and Continuous Predictors A Continuous Focal Independent Variable A Qualitative Focal Independent Variable Qualitative Variables with More than Two Levels Summary
 Chapter 4: Additional Considerations Selected Issues The BiLinear Nature of Interactions for Continuous Variables Calculating Coefficients of Focal Independent Variables at Different Moderator Values Partialing the Component Terms Transformations Multiple Interaction Effects Standardized and Unstandardized Coefficients Metric Properties Measurement Error Robust Analyses and Assumption Violations WithinSubject and RepeatedMeasure Designs Ordinal and Disordinal Interactions Regions of Significance Confounded Interactions Optimal Experimental Designs and Statistical Power Covariates Control for Experimentwise Errors Omnibus Tests and Interaction Effects Some Common Misapplications Interaction Models with Clustered Data and Random Coefficient Models Continuous Versus Discrete Predictor Variables The Moderator Framework Revisited References Notes About the Authors.
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16. Interaction effects in logistic regression [2001]
 Jaccard, James.
 Thousand Oaks, Calif. : Sage Publications, c2001.
 Description
 Book — vii, 70 p. : ill. ; 21 cm.
 Summary

 Introduction Interactions between Qualitative Predictors Interactions between Qualitative and Quantitative/Continuous Predictors Interactions between Quantitative/Continuous Predictors Multicategory Models Additional Considerations.
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 Welkowitz, Joan.
 5th ed.  Fort Worth : Harcourt Brace College Publishers, c2000.
 Description
 Book — xvii, 359 p. : ill. ; 24 cm.
 Online
Education Library (Cubberley)
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18. Logistic regression : a primer [2000]
 Pampel, Fred C.
 Thousand Oaks, Calif. : Sage Publications, c2000.
 Description
 Book — vii, 86 p. : ill. ; 22 cm.
 Summary

 The Logic of Logistic Regression Interpreting Logistic Regression Coefficients Estimation and Model Fit Probit Analysis Conclusion.
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 Nicol, Adelheid A. M.
 4th print., with updates.  Washington, DC : American Psychological Association, c1999.
 Description
 Book — vii, 157 p. : ill. ; 26 cm.
 Summary

 Analysis of Covariance (ANCOVA) Analysis of Variance (ANOVA) Canonical Corrlation Chi Square Cluster Analysis Correlation Discriminant Function Analysis Factor Analysis Frequency and Demographics Logistic Regression Loglinear Analysis Means MetaAnalysis Multiple Regression Multivariate Analysis of Covariance (MANCOVA) Multivariate Analysis of Variance (MANOVA) PostHoc and APriori Test of Means Structural Equation Modelling TTest of Means Word.
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20. Basics of qualitative research : techniques and procedures for developing grounded theory [1998]
 Strauss, Anselm L.
 2nd ed.  Thousand Oaks : Sage Publications, c1998.
 Description
 Book — xiii, 312 p. : ill. ; 23 cm.
 Summary

 PART ONE: BASIC CONSIDERATIONS Introduction Description, Conceptual Ordering, and Theorizing The Interplay between Qualitative and Quantitative in Theorizing Practical Considerations PART TWO: CODING PROCEDURES Analysis Through Microscopic Examination of Data Basic Operations Asking Questions and Making Comparisons Analytic Tools Open Coding Axial Coding Selective Coding Coding for Process The Conditional/Consequential Matrix Theoretical Sampling Memos and Diagrams PART THREE: GAINING CLOSURE Writing Theses and Monographs and Giving Talks about Research Criteria for Evaluation Student Questions and Answers to These.
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