Empirical Direction in Design and Analysis

By Norman H. Anderson | Go to book overview

NOTES
14.1.1a
Unreported subject loss troubled some work on the “poopout effect, ” in which rats learn a shock-avoidance response but then gradually cease to avoid at the warning signal, instead waiting until the shock comes on to make an escape response (Anderson & Nakamura, 1964). Quite a few rats, however, did not learn the avoidance at all.

In writing up some subsequent experiments, we had considerable trouble relating our results to a published paper that reported avoidance conditioning but not any subjects that failed to learn. When I later saw one of the authors at a meeting, he said they actually had thrown out a lot of rats that had failed to learn. He seemed unaware that their failure to mention this subject elimination in their article might mislead others.

14.1.1b
An example of filling in missing responses arose in a functional measurement analysis of a mental search task by Shanteau (1991). Subjects began by thoroughly memorizing this serial list of eight four-letter words:

rice, lime, tuna, beef, fish, pear, cake, veal

They were then asked various questions that had some, none, or all of the words as answers. Among these questions were:

Which have exactly two vowels?

Which have exactly two consonants?

Their task was to process the memorized list serially, speaking correct answers aloud.

The sequence of response times followed an additive model that demonstrated the independence of the two primary processes: memory retrieval; and the decision whether a given word was an answer. The decision processing times could be quantified with this model. As one interesting result, decision time for the listed consonant question was twice as long as for the vowel question although the two have identical answers.

Occasionally, a subject failed to speak a correct answer. In order to complete the data curve, the mean latency for the other subjects was substituted in these cases. Such missing responses occurred about 3% of the time in the later experiments, a frequency that seems not unreasonable for this particular task. Various checks indicated that this substitution procedure did not bias the results. Extremely long response times occurred about 1 time in 200 and were replaced in a similar manner.

This experiment is one of many in which within subject replication would be desirable. This would have eased the missing data problem and, more important, allowed assessment of individual differences through single subject analysis.

14.1.1c
The following example of extreme scores is a lesson in experimental procedure as well as the principle of replication. In this study, subjects had to evaluate each of a sequence of stimuli on a low-to-high rating scale. A substantial number of subjects switched their scale direction partway through, thus interchanging low and high. This switch was clear in the data because many stimuli were clearly low or high. My assistant had not monitored the subjects' behavior after they got started in the experiment and, because the subjects were being run under time pressure at another institution, transcribing responses was deferred until subject running was complete. Thus, the problem was not noticed until all 96 subjects had been run one by one. Because the switch was clear in the data, it was easy to detect and replace these subjects and this was done.

-431-

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Empirical Direction in Design and Analysis
Table of contents

Table of contents

  • Title Page iii
  • Dedication v
  • Foreword vi
  • Contents vii
  • Preface xvi
  • Chapter 1 - Scientific Inference 1
  • Preface 30
  • Chapter 2 - Statistical Inference 31
  • How to Do Exercises 54
  • Exercises for Chapter 2 54
  • Preface 58
  • Chapter 3 - Elements of Analysis of Variance I 59
  • Notes 75
  • Appendix: How to Randomize 77
  • Exercises for Chapter 3 84
  • Preface 90
  • Chapter 4 - Elements of Analysis of Variance II 91
  • Notes 111
  • Exercises for Chapter 4 113
  • Preface 118
  • Chapter 5 - Factorial Design 119
  • Notes 145
  • Appendix: Hand Calculation for Factorial Design 148
  • Exercises for Chapter 5 151
  • Preface 158
  • Chapter 6 - Repeated Measures Design 159
  • Notes 177
  • Exercises for Chapter 6 181
  • Preface 188
  • Chapter 7 - Understanding Interactions 189
  • Notes 209
  • Exercises for Chapter 7 214
  • Preface 218
  • Chapter 8 - Confounding 219
  • Notes 250
  • Preface 258
  • Chapter 9 - Regression and Correlation 259
  • Notes 280
  • Exercises for Chapter 9 282
  • Preface 286
  • Chapter 10 - Frequency Data and Chi-Square 287
  • Notes 300
  • Exercises for Chapter 10 302
  • Preface 306
  • Chapter 11 - Single Subject Design 307
  • Notes 338
  • Exercises for Chapter 11 345
  • Preface 350
  • Chapter 12 - Nonnormal Data and Unequal Variance 351
  • Notes 373
  • Exercises for Chapter 12 378
  • Preface 382
  • Chapter 13 - Analysis of Covariance 383
  • Notes 395
  • Exercises for Chapter 13 397
  • Preface 400
  • Chapter 14 - Design Topics I 401
  • Notes 431
  • Exercises for Chapter 14 437
  • Preface 442
  • Chapter 15 - Design Topics II 443
  • Notes 475
  • Exercises for Chapter 15 481
  • Preface 484
  • Chapter 16 - Multiple Regression 485
  • Notes 514
  • Exercises for Chapter 16 520
  • Preface 524
  • Chapter 17 - Multiple Comparisons 525
  • Notes 546
  • Exercises for Chapter 17 548
  • Preface 550
  • Chapter 18 - Sundry Topics 551
  • Notes 589
  • Exercises for Chapter 18 596
  • Preface 602
  • Chapter 19 - Foundations of Statistics 603
  • Notes 637
  • Preface 646
  • Chapter 20 - Mathematical Models for Process Analysis 647
  • Notes 677
  • Exercises for Chapter 20 681
  • Preface 688
  • Chapter 21 - Toward Unified Theory 689
  • Notes 729
  • Exercises for Chapter 21 742
  • Preface 750
  • Chapter 22 - Principles and Tactics of Writing Papers 751
  • Notes 761
  • Preface 764
  • Chapter 23 - Lifelong Learning 765
  • Notes 780
  • Preface 782
  • Chapter 0 - Basic Statistical Concepts 783
  • Notes 803
  • Exercises for Chapter 0 805
  • Statistical Tables 808
  • References 820
  • Author Index 847
  • Subject Index 854
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