## The Design and Analysis of Research StudiesThis book provides graduate students and research workers in the biological, medical and social sciences with the statistical background needed to collect and analyse data in an intelligent and critical manner. |

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### Contents

Preview | 1 |

13 Bias and confounding in observational studies | 4 |

14 The sample survey | 12 |

16 Experiments and quasiexperiments | 13 |

17 Ethical considerations | 15 |

18 Planning and carrying out a research study | 16 |

The sample survey | 17 |

22 Simple random sampling | 19 |

The Lanarkshire milk experiment | 163 |

Interrupted time series | 167 |

62 Analysis with the interrupted time series design | 168 |

63 Analysis with the comparative time series design | 175 |

64 Summary and further reading | 177 |

Exercises | 178 |

Fluoridation in Birmingham | 182 |

More advanced experimental designs | 188 |

23 The distribution of sample means | 20 |

24 Estimation of totals and proportions | 23 |

25 Determining sample sizes with simple random sampling | 26 |

26 Stratified sampling | 28 |

27 Sample size allocation for stratified samples | 30 |

28 Stratified sampling for proportions | 32 |

29 Poststratification | 33 |

210 Quota sampling | 34 |

212 Cluster sampling | 37 |

213 Systematic sampling | 38 |

214 Multistage sampling | 39 |

215 Nonsampling errors | 40 |

216 Biased procedures | 41 |

217 Bias introduced during data collection | 42 |

218 Processing errors | 43 |

220 Designing a questionnaire | 44 |

221 Summary and further reading | 46 |

Exercises | 47 |

Checklist for planning a sample survey | 57 |

Other sampling designs | 58 |

33 Removal sampling | 62 |

34 Transect sampling | 66 |

36 Sampling positions of objects in space | 68 |

37 Distancebased methods | 70 |

38 Quadrat counts | 75 |

39 Sampling of quadrats | 77 |

310 Summary and further reading | 78 |

Exercises | 79 |

Site location in prehistoric Thailand | 82 |

The linear regression model | 87 |

43 Estimation and tests with simple linear regression | 88 |

44 Multiple linear regression | 92 |

45 The extra sum of squares principle | 94 |

46 Assessing the assumptions of a regression model | 98 |

47 Residual plots | 100 |

48 Tests on residuals | 107 |

49 The DurbinWatson lest | 108 |

410 Summary and further reading | 112 |

Exercises | 113 |

The loss of sales in a store due to a fire | 120 |

Experimental designs to assess the effect of a treatment | 132 |

52 External and internal validity | 133 |

53 Pseudoreplication | 135 |

54 The onegroup pretestposttest design | 137 |

55 The static group comparison | 138 |

56 The importance of a comparable control group | 139 |

57 Regression to the mean | 140 |

58 The comparative posttest design | 142 |

59 The comparative change design | 144 |

510 The comparative change design without randomization | 148 |

512 Regression adjustments for confounding variables | 152 |

513 Matching | 156 |

514 Summary and further reading | 161 |

73 Some general considerations | 194 |

74 Transformation of data | 199 |

75 Experiments with three or more factors | 201 |

76 Higher order interactions | 204 |

77 Blocking | 205 |

78 Latin squares | 208 |

79 Nested factors | 209 |

710 Splitplot experiments in agricultural research | 210 |

711 Other uses of the splitplot design | 213 |

712 Repeated measures experiments | 215 |

713 The assumption of compound symmetry | 217 |

714 Analysis of variance by multiple regression | 219 |

715 Ancillary analyses | 224 |

716 Summary and further reading | 225 |

An experiment on lockstitch seams | 227 |

Some special types of data | 234 |

82 The analysis of count data | 236 |

83 Chisquared tests on count data | 237 |

84 McNemars test for correlated proportions | 242 |

85 Loglinear models | 244 |

86 Extraneous variance | 252 |

87 Using base rates | 253 |

88 The analysis of proportion data | 255 |

89 Survival data | 261 |

810 Generalized linear modelling | 263 |

811 Multivariate data | 264 |

812 Summary and further reading | 266 |

Exercises | 267 |

The location of prehistoric Maya sites | 270 |

Computer intensive statistics | 286 |

92 Randomization tests | 288 |

93 Determining the number of randomizations required | 292 |

94 Confidence limits by randomization | 293 |

95 Monte Carlo tests | 294 |

96 Jackknifing | 298 |

97 Bootstrapping | 302 |

98 Summary and further reading | 304 |

Exercise | 305 |

Ethical considerations | 312 |

103 Obligations to funders and employers | 313 |

104 Obligations to colleagues | 314 |

106 Experiments on animals | 316 |

A clinical trial on ECMO | 317 |

Synthesis carrying out a research study | 321 |

113 Planning the collection of data | 324 |

114 Sample size determination | 325 |

115 Collecting data | 334 |

117 The research report | 335 |

336 | |

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348 | |

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### Common terms and phrases

allow analysis of variance approximately assess assumption bootstrap calculated cancer death rates Chapter chi-squared cluster coefficients compared confidence interval considered control group degrees of freedom different from zero discussed dummy variables ECMO estimated standard error evidence example expected frequencies experimental design experimental units F-ratio factor Figure fluoridation indicates interaction involves linear regression log-linear model logistic regression mean square measured month multiple regression nearest neighbour normal distribution obtained occur parameters patients percentage population mean possible posttest pretest probability problem proportion question random allocation random points randomization test randomly regression equation regression model replication residual plots sample mean sample sizes schools scores serial correlation sets of data shown in Table significance level significantly different significantly large simple random sample standard deviation standard error standardized residuals stratified sampling subjects sum of squares teaching methods tion total number treatment effect values variance table variation