Russel-Research-Method-in-Anthropology

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644 Chapter 20 data to test your theory. As replications accumulate for questions of importance in the social sciences, the question of statistical power becomes more and more important. So, what’s the right amount of statistical power to shoot for? Cohen (1992) recommends that researchers plan their work—that is, set the effect size they recognize as important, set the level of statistical significance they want to achieve (.05, for example, or .01), and calculate the sample size—in order to achieve a power of .80. A power value of .80 would be an 80% chance of recognizing that our original hypothesis is really true and a 20% chance of rejecting our hypothesis when it’s really true. If you shoot for a power level of much lower than .80, says Cohen, you run too high a risk of making a Type II error. On the other hand, power ratings much higher than .80 might require such large n’s that researchers couldn’t afford them (ibid.:156). If you want 90% power for a .01 (1%) two-tailed test of, say, the difference between two Pearson’s r’s, then, you’d need 364 participants (respondents, subjects) to detect a difference of .20 between the scores of the two groups. If you were willing to settle for 80% power and a .05 (5%) two-tailed test, then the number of participants drops to 192. (To find the sample size needed for any given level of power, see Kraemer and Theimann 1987:105–112.) The Shotgun Approach A closely related issue concerns ‘‘shotgunning.’’ This involves constructing a correlation matrix of all combinations of variables in a study, and then relying on tests of significance to reach substantive conclusions. Kunitz et al. (1981) studied the determinants of hospital utilization and surgery in 18 communities on the Navajo Indian Reservation during the 1970s. They measured 21 variables in each community, including 17 independent variables (the average education of adults, the percentage of men and women who worked full-time, the average age of men and women, the percentage of income from welfare, the percentage of homes that had bathrooms, the percentage of families living in traditional hogans, etc.) and four dependent variables (the rate of hospital use and the rates for the three most common types of surgery). Table 20.20 shows the correlation matrix of all 21 variables in this study. There are n(n1)/2 pairs in any list of items, so, for a symmetric matrix of 21 items there are 210 possible correlations. Kunitz et al. point out in the footnote to their matrix that, for n 18, the 0.05 level of probability corresponds to r 0.46 and the 0.01 level corresponds to r 0.56. By the Bonferonni correction, they could have expected:
TABLE 20.20 Correlation Matrix of All 21 Variables in Kunitz et al.’s Study of Hospital Use on the Navajo Reservation 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 1 Near hospital 2 Near surgery .67 3 Wage work .24 .09 4 Welfare .52 .46 .54 5 Education of men .42 .43 .73 .49 6 Education of women .01 .21 .67 .32 .81 7 Hogans .07 .37 .26 .72 .28 .40 8 Bathrooms .44 .57 .63 .63 .70 .64 .47 9 Household size .01 .16 .48 .24 .34 .07 .04 .12 10 Working women .35 .36 .68 .65 .65 .57 .48 .62 .22 11 Working men .24 .18 .73 .37 .73 .63 .16 .41 .45 .45 12 Vehicles .34 .08 .40 .17 .22 .52 .53 .29 .06 .31 .40 13 Median income .45 .51 .66 .60 .67 .60 .38 .79 .07 .83 .48 .27 14 Per capita income .25 .20 .68 .46 .61 .40 .15 .29 .68 .48 .51 .30 .47 15 Age of women .23 .03 .47 .15 .36 .66 .02 .46 .30 .37 .32 .56 .43 .04 16 Age of men .28 .15 .77 .31 .60 .55 .01 .67 .06 .51 .68 .35 .63 .45 .60 17 Age of patients .13 .47 .13 .14 .21 .15 .18 .22 .36 .04 .26 .15 .26 0.2 .29 .32 18 Hysterectomies .41 .48 .62 .55 .57 .46 .23 .75 .09 .45 .46 .39 .62 .59 .37 .62 0.28 19 Appendectomies .31 .40 .32 .14 .44 .33 .16 .51 .13 .07 .27 .01 .42 .35 .31 .49 .56 .62 20 Cholesystectomies .23 .70 .15 .43 .35 .34 .46 .68 .22 .19 .12 .31 .40 .14 .17 .17 .35 .70 .49 21 Hospital rate .49 .24 .02 .26 .02 .25 .09 .16 .19 .04 .34 .33 .01 .22 .43 0.16 .45 .17 .10 .18 N 18 0.46, p .05 0.56, p 0.01 SOURCE: Reprinted from Social Science and Medicine 15B, S. J. Kunitz et al., ‘‘Determinants of Hospital Utilization and Surgery on the Navajo Indian Reservation, 1972–1978,’’ pp. 71–79, 1981, with permission from Elsevier.
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H. Russell Bernard FOURTH EDITION R
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Research Methods in Anthropology Fo
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Contents Preface vii 1. Anthropolog
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Preface Since 1988, when I wrote th
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Preface ix sampling: why we do it a
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Preface xi 21, you will be able to
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Preface xiii testimony. There is an
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Preface xv begin writing the second
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1 ◆ Anthropology and the Social S
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Anthropology and the Social Science
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The Foundations of Social Research
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3 ◆ Preparing for Research Settin
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Preparing for Research 71 research
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Preparing for Research 73 morning u
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Preparing for Research 75 the AAA b
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Preparing for Research 77 showed wh
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Preparing for Research 79 That will
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Preparing for Research 81 mothers.
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Preparing for Research 83 gathering
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Preparing for Research 85 hypothesi
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Preparing for Research 87 I mention
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Preparing for Research 89 A Guide t
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Preparing for Research 91 people re
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Preparing for Research 93 Observed
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Preparing for Research 95 dent. (Re
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The Literature Search 97 too busy t
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The Literature Search 99 year, who
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The Literature Search 101 like demo
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The Literature Search 103 reports e
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The Literature Search 105 gists, in
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The Literature Search 107 Women Sca
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5 ◆ Research Design: Experiments
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Research Design: Experiments and Ex
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Sampling 147 ried around here deliv
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Sampling 149 the potential sampling
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Sampling 151 they’re joined by al
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Sampling 153 116. If the first rand
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Sampling 155 off base in our thinki
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Sampling 157 Cluster Sampling and C
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Sampling 159 Probability Proportion
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Sampling 161 you will properly surv
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Sampling 163 the cluster, the large
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Sampling 165 TABLE 6.2 Comparison o
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Sampling 167 25 Number of Household
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7 ◆ Sampling Theory Distributions
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Sampling Theory 171 In normal distr
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Sampling Theory 173 a lot of inform
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Sampling Theory 175 TABLE 7.2 All S
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Sampling Theory 177 12 10 Number of
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Sampling Theory 179 Calculating Sam
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Sampling Theory 181 Look up what’
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Sampling Theory 183 and we solve fo
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Sampling Theory 185 ables combine t
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Nonprobability Sampling and Choosin
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TABLE 8.4 Matches, Proportions of M
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Interviewing: Unstructured and Semi
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10 ◆ Structured Interviewing I: Q
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Structured Interviewing I: Question
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11 ◆ Structured Interviewing II:
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Structured Interviewing II: Cultura
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Scales and Scaling 319 10 times, or
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Scales and Scaling 321 students’
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Scales and Scaling 323 points. The
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Scales and Scaling 325 TABLE 12.2a
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Scales and Scaling 327 wealth in vi
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Scales and Scaling 329 You may obse
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Scales and Scaling 331 interitem co
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Scales and Scaling 333 ality of a s
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Scales and Scaling 335 TABLE 12.7 T
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Scales and Scaling 337 Having a Col
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Scales and Scaling 339 The Cantril
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Scales and Scaling 341 and has been
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Participant Observation 343 Romanci
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Participant Observation 345 sion, s
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Participant Observation 347 doses o
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Participant Observation 349 great s
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Participant Observation 351 less—
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Participant Observation 353 oped by
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Participant Observation 355 Graham
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Participant Observation 357 ters fr
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Participant Observation 359 washing
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Participant Observation 361 that yo
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Participant Observation 363 ‘‘c
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Participant Observation 365 hall wh
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Participant Observation 367 Maintai
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Participant Observation 369 not to
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Participant Observation 371 pletely
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Participant Observation 373 changed
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Participant Observation 375 Besides
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Participant Observation 377 Thomas
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Participant Observation 379 But not
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Participant Observation 381 baby’
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Participant Observation 383 into fo
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Participant Observation 385 in Mace
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14 ◆ Field Notes: How to Take The
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Field Notes: How to Take Them, Code
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15 ◆ Direct and Indirect Observat
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16 ◆ Introduction to Qualitative
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Introduction to Qualitative and Qua
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START: SEARCH WHOLESALE MARKET FOR
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17 ◆ Qualitative Data Analysis I:
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Qualitative Data Analysis I: Text A
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19 ◆ Univariate Analysis The next
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Univariate Analysis 551 But if you
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Univariate Analysis 553 TABLE 19.1
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Univariate Analysis 555 Notice in t
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Univariate Analysis 559 TABLE 19.3b
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Univariate Analysis 561 possible an
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Univariate Analysis 563 people hang
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Univariate Analysis 573 Number of C
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Univariate Analysis 575 some basic
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Univariate Analysis 577 interquarti
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Univariate Analysis 579 countries t
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Univariate Analysis 581 Both groups
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Univariate Analysis 585 would be no
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Univariate Analysis 587 rejecting H
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Univariate Analysis 589 lation, 68.
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Univariate Analysis 591 of Shipibo
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Page 673 and 674: TABLE 21.11 Wealth by Education, Co
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Page 705 and 706: Multivariate Analysis 687 1.71 1.32
Page 707 and 708: Multivariate Analysis 689 ‘‘chi
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Multivariate Analysis 695 just beca
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698 Appendix A 32179 00597 87379 25
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APPENDIX B Table of Areas under a N
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702 Appendix B (A) (B) (C) (A) (B)
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APPENDIX D Chi-Square Distribution
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APPENDIX E F Table for the .05 Leve
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708 Appendix E F Table for the .01
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APPENDIX F Resources for Fieldworke
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712 References obesity in Saudi Ara
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714 References Beautrais, A. L., P.
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716 References the self-assessment
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718 References Bradburn, N. M. 1983
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720 References ments by considering
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722 References ing in reflected glo
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724 References village. In Self, se
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726 References Duncan, O. D. 1966.
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728 References achieve high respons
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730 References Gatz, M., and M. Hur
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732 References C2KBR/01-1. Washingt
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734 References study of relationshi
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736 References Hornik, J., and S. E
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738 References esses in survey rese
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740 References Kessler, R. C., and
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742 References Laban Moogi Gwako, E
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744 References Lewis, R. B. 2004. N
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746 References McCall, G. 1978. Obs
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748 References Morgan, D. L. 1997.
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750 References Oakhill, J., and A.
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752 References Piliavin, I. M., J.
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754 References nicity-of-interviewe
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756 References Rotton, J., and M. S
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758 References Schwarts, N. A. 2004
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760 References Smith, L. D. 1986. B
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762 References Stricker, L. J. 1988
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764 References pharmacists in HIV/S
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766 References Webb, E. J., D. T. C
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768 References Williams, T. 1996. E
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Subject Index Numbers in italics re
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Subject Index 773 Campos, Alberto,
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Subject Index 775 data analysis, 45
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Subject Index 777 external states,
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Subject Index 779 individual attrib
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Subject Index 781 median, 562, 563-
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Subject Index 783 parsimony, princi
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Subject Index 785 random digit dial
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Subject Index 787 simple scales, 31
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Subject Index 789 T-scores, 591 t-t
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Author Index Numbers in italics ref
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Author Index 793 Choi, N., 33 Choms
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Author Index 795 Gregson, S., 93 Gr
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Author Index 797 Leap, W., 376 LeCo
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Author Index 799 Rashid, R. G., 121
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Author Index 801 Vadez, V., 55, 93
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