Psychological research methods: a conceptual approach
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Boston u.a.
Allyn and Bacon
1985
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | Literaturverz. S. 500 - 512 |
| Beschreibung: | XX, 538 S. graph. Darst. |
| ISBN: | 0205083811 |
Internformat
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| 245 | 1 | 0 | |a Psychological research methods |b a conceptual approach |c Harold O. Kiess ; Douglas W. Bloomquist |
| 264 | 1 | |a Boston u.a. |b Allyn and Bacon |c 1985 | |
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Datensatz im Suchindex
| _version_ | 1804119460551852032 |
|---|---|
| adam_text | Titel: Psychological research methods
Autor: Kiess, Harold O.
Jahr: 1985
Contents
Preface xv
To the Student xix
1 WHY UNDERSTAND PSYCHOLOGICAL RESEARCH METHODS 2
Preview 2
Why You Need to Know This Material 2
A Skeptical View of Knowledge 3
An Empirical Base of Knowledge 6
Excitement of Research 7
A Consumer of Research 7
Who Does Psychological Research? 8
Ethical Principles for Research with Human Participants 9
Ethical Principles for the Care and Use of Animals 12
Example of Psychological Research 14
Summary 21
2 THE BASIS OF PSYCHOLOGICAL RESEARCH 22
Preview 22
Why You Need to Know This Material 22
Choosing a Research Problem 23
Characteristics of Scientific Research 25
Causality 25
Empirical knowledge 26
Replicability 26
Role of Theory and Research Hypotheses 27
What is psychological theory? 27
Research hypotheses 29
vii
viii Contents
Empirical evaluation of theories and research hypotheses 32
Current theorizing in psychology 36
Usefulness of theories in psychological research: pro and con 37
Applying the criteria of science: parapsychology 40
The Empirical Test 41
Summary 41
3 FUNDAMENTALS OF EXPERIMENTAL DESIGN 42
Preview 42
Why You Need to Know This Material 42
Variables of Psychological Research 43
Independent variables 43
Dependent variables 44
Extraneous variables 45
Variables as Constructs 47
Concepts and constructs 47
Empirical referents 48
Operational definitions 48
Difference between conceptual variables and
operationally defined variables 53
Variables as either independent or dependent 53
The Experiment 54
Control and experimental conditions 54
Confounding 55
The Basics of Experimental Design 57
Number of independent variables employed 58
Between-Subjects and within-subjects designs 58
One-Factor Between-Subjects Designs 59
The true experiment 59
Ex post facto studies 61
Summary 66
4 DESIGNING AND CONDUCTING AN EXPERIMENT 68
Preview 68
Why You Need to Know This Material 68
Effects of Extraneous Variables 69
Confounding 69
Error variation 70
Strategy of Experimental Design 75
Maximizing variation due to the independent variable 75
Minimizing variation due to extraneous variables 78
Techniques for controlling effects of extraneous variables 78
Contents ix
Conducting the Experiment 89
How many participants should be used? 89
Pilot studies: ensuring that the experiment can be run 90
Summary 91
5 MEASUREMENT AND DESCRIPTIVE ANALYSIS OF DATA 92
Preview 92
Why You Need to Know This Material 92
Measurement 93
Reliability 94
Validity 94
Levels of measurement 95
Rating scales and level of measurement 102
Treatment of Raw Data from an Experiment 104
What do the raw data tell us? 106
Organizing the raw data 107
Shapes of frequency distributions 110
Descriptive Statistics 112
Need for statistics 112
Measures of central tendency 114
When a mean is not the mean: the geometric mean 118
Summary 120
6 MEASURES OF VARIABILITY AND ESTIMATION OF
POPULATION PARAMETERS 122
Preview 122
Why You Need to Know This Material 122
Need for Measures of Variability 123
Measures of Variability 124
Range 124
Interquartile range 125
Semi-interquartile range 126
Comparing range measures 126
Average deviation 126
Variance and the standard deviation 128
What does the standard deviation tell us? 131
Comparing measures of variability 135
Choosing Descriptive Statistics 136
Level of measurement of the dependent variable 137
Shape of the frequency distribution 138
Using descriptive statistics for further analysis of data 139
x Contents
Exploratory Data Analysis 140
Stem-and-leaf displays 140
Box-and-whisker plots 141
Using Statistics for Inference and Estimation 142
Sample mean as an estimator of population mean 143
Summary 154
7 STATISTICAL HYPOTHESIS TESTING AND THE t TEST 156
Preview 156
Why You Need to Know This Material 156
The Experimenter s Dilemma 157
Numerical illustration of the experimenter s dilemma 158
Statistical hypothesis testing: resolving the experimenter s dilemma 161
Statistical hypothesis testing 162
Statistical model for an experiment 162
Statistical tests 163
The t Test for Independent Groups 173
Sampling distribution of differences in sample means 174
Statistical decision making with a t test for independent groups 177
Mann-Whitney [/Test 189
Perception of ambiguous figures: an example experiment 190
Summary 197
8 ONE-FACTOR BETWEEN-SUBJECTS ANALYSIS OF VARIANCE 200
Preview 200
Why You Need to Know This Material 200
Overview of Analysis of Variance 201
Analysis of Variance Statistical Model 202
Constructing a score 202
Deriving variance estimates from the components of scores 205
Summarizing an analysis of variance 210
Mean squares as estimates of the population variance 211
Statistical decision making with analysis of variance 217
Analysis of Variance and Principles of Research Design 223
Analysis of Variance on the Data of McCarthy and Betz 224
Relationship between t and F 225
Summary 226
9 ONE-FACTOR MULTILEVEL DESIGNS: ANALYSIS OF VARIANCE,
FOLLOW-UP TESTS, AND STRENGTH OF ASSOCIATION
MEASURES 228
Preview 228
Why You Need to Know This Material 228
Contents xi
Tonic Immobility as a Research Problem 230
Example of a Multilevel One-Factor Design 231
Analyzing data of a multilevel experiment 232
Multiple Comparison Procedures 235
A simple comparison 236
Problem of Type I errors 236
Planned vs. post hoc comparisons 237
Comparison procedure for multiple F tests 238
Post hoc comparisons and control of Type I errors 240
Choosing a test of multiple comparisons 242
Multiple comparisons on the tonic immobility experiment 242
Pitfalls of Data Fishing 244
Strength of a Treatment Effect 245
Measuring strength of association with a significance test 245
Measures of strength of association 246
Examples of using strength of association measures 247
Interpreting measures of the strength of association 248
Kruskal- Wallis analysis of variance by ranks 250
Summary 254
10 FACTORIAL DESIGNS AND TWO-WAY ANALYSIS OF VARIANCE 256
Preview 256
Why You Need to Know This Material 256
Factorial Designs 257
The 2X2 Between-Subjects Design 258
Information obtained from a factorial design 259
Importance of factorial designs and interactions 260
Example of a 2 X 2 Between-Subjects Design 262
Descriptive data analysis of a factorial experiment 263
Inferential Data Analysis of a Factorial Design 265
An overview 265
Components of a score 265
Deriving variance estimates from the components of scores 267
Mean squares as estimates of the population variance 271
Statistical decision making with factorial analysis of variance 272
Analysis of variance on the example data 273
Interpreting an analysis of variance 276
Extensions of the 2 X 2 Design 286
Number of subjects required 286
Analysis of variance 286
Follow-up Tests for the Analysis of Variance 288
Follow-up tests for statistically significant main effects 288
Follow-up tests for a statistically significant interaction 288
xii Contents
Types of Independent Variables in Factorial Designs 290
Examples of various types of between-subjectsfactorial designs 291
Summary 296
11 ONE-FACTOR WITHIN-SUBJECTS DESIGNS AND ANALYSIS
OF VARIANCE 298
Preview 298
Why You Need to Know This Material 298
Example of a Within-Subjects Experiment 299
Characteristics of Within-Subjects Designs 300
Number of participants required 301
Sensitivity of within-subjects designs 301
Multiple-treatment effects 302
Analyzing Data of a One-Factor Within-Subjects Design 310
Descriptive analysis of data 311
One-factor within-subjects analysis of variance 311
Analysis of variance on the data from the example 318
The t Test for Related Measures 322
Choice of Research Design: Between-Subjects or Within-Subjects 323
Multiple-treatment effects 323
Statistical considerations 326
The research hypothesis 329
Nonparametric Statistical Analyses for One-Factor Within-Subjects Designs 329
An experimental example 330
Wilcoxon signed-ranks test 331
Friedman analysis of variance by ranks 333
SvaaM-N Designs: A Special Case of the Within-Subjects Design 335
Reversal design 336
Characteristics of reversal designs 337
Analyzing data for reversal designs 340
Summary 340
12 TWO-FACTOR WITHIN-SUBJECTS AND MIXED DESIGNS AND
ANALYSES OF VARIANCE 342
Preview 342
Why You Need to Know This Material 342
Two-Factor Within-Subjects Design 343
Characteristics of within-subjects factorial designs 344
Descriptive analysis of data 345
Two-factor within-subjects analysis of variance 346
Example of a two-factor within-subjects experiment 358
Contents xiii
Two-Factor Mixed Design 361
Characteristics of a mixed factorial design 362
Descriptive analysis of data 363
Two-factor mixed-design analysis of variance 363
Example of a two-factor mixed experiment 373
Comparison of Factorial Designs 375
Type of independent varables that may be used 375
Number of participants required 375
Sensitivity to multiple-treatment effects 375
Statistical sensitivity to treatment effects 376
Summary 378
13 VALIDITY OF EXPERIMENTS 380
Preview 380
Why You Need to Know This Material 380
Role of Replication in Establishing Validity 382
Types of replication 382
Statistical-Conclusion Validity 383
Factors affecting statistical-conclusion validity 384
When is statistical-conclusion validity achieved? 388
Internal Validity 390
Threats to internal validity of experiments 390
When is internal validity achieved? 392
Construct Validity 393
Theoretical constructs 393
Development of empirical referents 394
Threats to construct validity of experiments 395
When is construct validity achieved? 399
External Validity 400
Population validity 400
Ecological validity 406
When is external validity achieved? 407
Some Concluding Comments on Validity 407
Scientific Understanding 409
Is There a Sex Bias in Psychological Research? 410
Choice of research topics 410
Participants employed 411
Empirical referents used 411
Statistically testing for sex differences 412
Conclusions reached from the results 412
What can be done? 412
Summary 413
xiv Contents
14 NONEXPERIMENTAL RESEARCH METHODS 414
Preview 414
Why You Need to Know This Material 414
Correlational Approaches to Research 415
Pearson product-moment correlation coefficient 418
Spearman rank-order correlation coefficient 426
Ex post facto study as correlational research 428
Correlation and causality 430
Naturalistic Observation 431
Observation in naturalistic observation 432
Example of naturalistic observation 433
Case-Study Method 437
Characteristics of the case study 438
Example of a case study 439
Value of case studies 439
Analysis-of-Frequency Data: The CHI Square Test 443
Example employing a CHI Square analysis 443
Computing the x2 statistic 445
Correcting for continuity in a 2 X 2 contingency table 446
Limitations on use of a CHI Square Test 446
Summary 447
15 WRITING THE RESEARCH REPORT 448
Preview 448
Why You Need to Know This Material 448
Overview of a Research Report 450
Title 450
Abstract 451
Introduction 451
Method 455
Results 458
Discussion 461
References 463
Appendix 464
Summary 465
Sample Laboratory Report 466
References 500
Appendix 513
Name Index 525
Subject Index 531
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| spelling | Kiess, Harold O. Verfasser aut Psychological research methods a conceptual approach Harold O. Kiess ; Douglas W. Bloomquist Boston u.a. Allyn and Bacon 1985 XX, 538 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Literaturverz. S. 500 - 512 Psychologie - Recherche Psychology Psychology Research Research Design Psychologie (DE-588)4047704-6 gnd rswk-swf Forschungsmethode (DE-588)4155046-8 gnd rswk-swf Psychologie (DE-588)4047704-6 s Forschungsmethode (DE-588)4155046-8 s DE-604 Bloomquist, Douglas W. Verfasser aut HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=003283493&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Kiess, Harold O. Bloomquist, Douglas W. Psychological research methods a conceptual approach Psychologie - Recherche Psychology Psychology Research Research Design Psychologie (DE-588)4047704-6 gnd Forschungsmethode (DE-588)4155046-8 gnd |
| subject_GND | (DE-588)4047704-6 (DE-588)4155046-8 |
| title | Psychological research methods a conceptual approach |
| title_auth | Psychological research methods a conceptual approach |
| title_exact_search | Psychological research methods a conceptual approach |
| title_full | Psychological research methods a conceptual approach Harold O. Kiess ; Douglas W. Bloomquist |
| title_fullStr | Psychological research methods a conceptual approach Harold O. Kiess ; Douglas W. Bloomquist |
| title_full_unstemmed | Psychological research methods a conceptual approach Harold O. Kiess ; Douglas W. Bloomquist |
| title_short | Psychological research methods |
| title_sort | psychological research methods a conceptual approach |
| title_sub | a conceptual approach |
| topic | Psychologie - Recherche Psychology Psychology Research Research Design Psychologie (DE-588)4047704-6 gnd Forschungsmethode (DE-588)4155046-8 gnd |
| topic_facet | Psychologie - Recherche Psychology Psychology Research Research Design Psychologie Forschungsmethode |
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