- •Contents
- •Preface to the 2nd Edition
- •Preface to the 1st Edition
- •Introduction
- •Learning Objectives
- •Variables and Data
- •The good, the Bad, and the Ugly – Types of Variable
- •Categorical Variables
- •Metric Variables
- •How can I Tell what Type of Variable I am Dealing with?
- •2 Describing Data with Tables
- •Learning Objectives
- •What is Descriptive Statistics?
- •The Frequency Table
- •3 Describing Data with Charts
- •Learning Objectives
- •Picture it!
- •Charting Nominal and Ordinal Data
- •Charting Discrete Metric Data
- •Charting Continuous Metric Data
- •Charting Cumulative Data
- •4 Describing Data from its Shape
- •Learning Objectives
- •The Shape of Things to Come
- •5 Describing Data with Numeric Summary Values
- •Learning Objectives
- •Numbers R us
- •Summary Measures of Location
- •Summary Measures of Spread
- •Standard Deviation and the Normal Distribution
- •Learning Objectives
- •Hey ho! Hey ho! It’s Off to Work we Go
- •Collecting the Data – Types of Sample
- •Types of Study
- •Confounding
- •Matching
- •Comparing Cohort and Case-Control Designs
- •Getting Stuck in – Experimental Studies
- •7 From Samples to Populations – Making Inferences
- •Learning Objectives
- •Statistical Inference
- •8 Probability, Risk and Odds
- •Learning Objectives
- •Calculating Probability
- •Probability and the Normal Distribution
- •Risk
- •Odds
- •Why you can’t Calculate Risk in a Case-Control Study
- •The Link between Probability and Odds
- •The Risk Ratio
- •The Odds Ratio
- •Number Needed to Treat (NNT)
- •Learning Objectives
- •Estimating a Confidence Interval for the Median of a Single Population
- •10 Estimating the Difference between Two Population Parameters
- •Learning Objectives
- •What’s the Difference?
- •Estimating the Difference between the Means of Two Independent Populations – Using a Method Based on the Two-Sample t Test
- •Estimating the Difference between Two Matched Population Means – Using a Method Based on the Matched-Pairs t Test
- •Estimating the Difference between Two Independent Population Proportions
- •Estimating the Difference between Two Independent Population Medians – The Mann–Whitney Rank-Sums Method
- •Estimating the Difference between Two Matched Population Medians – Wilcoxon Signed-Ranks Method
- •11 Estimating the Ratio of Two Population Parameters
- •Learning Objectives
- •12 Testing Hypotheses about the Difference between Two Population Parameters
- •Learning Objectives
- •The Research Question and the Hypothesis Test
- •A Brief Summary of a Few of the Commonest Tests
- •Some Examples of Hypothesis Tests from Practice
- •Confidence Intervals Versus Hypothesis Testing
- •Nobody’s Perfect – Types of Error
- •The Power of a Test
- •Maximising Power – Calculating Sample Size
- •Rules of Thumb
- •13 Testing Hypotheses About the Ratio of Two Population Parameters
- •Learning Objectives
- •Testing the Risk Ratio
- •Testing the Odds Ratio
- •Learning Objectives
- •15 Measuring the Association between Two Variables
- •Learning Objectives
- •Association
- •The Correlation Coefficient
- •16 Measuring Agreement
- •Learning Objectives
- •To Agree or not Agree: That is the Question
- •Cohen’s Kappa
- •Measuring Agreement with Ordinal Data – Weighted Kappa
- •Measuring the Agreement between Two Metric Continuous Variables
- •17 Straight Line Models: Linear Regression
- •Learning Objectives
- •Health Warning!
- •Relationship and Association
- •The Linear Regression Model
- •Model Building and Variable Selection
- •18 Curvy Models: Logistic Regression
- •Learning Objectives
- •A Second Health Warning!
- •Binary Dependent Variables
- •The Logistic Regression Model
- •19 Measuring Survival
- •Learning Objectives
- •Introduction
- •Calculating Survival Probabilities and the Proportion Surviving: the Kaplan-Meier Table
- •The Kaplan-Meier Chart
- •Determining Median Survival Time
- •Comparing Survival with Two Groups
- •20 Systematic Review and Meta-Analysis
- •Learning Objectives
- •Introduction
- •Systematic Review
- •Publication and other Biases
- •The Funnel Plot
- •Combining the Studies
- •Solutions to Exercises
- •References
- •Index
Index
α see significance level |
statistical significance 176–7 |
absolute risk 100–1, 106–7 |
strength 174, 175–80 |
absolute risk reduction (ARR) 106–7 |
see also scatterplots |
adjustment |
attitudes 77 |
confidence intervals 136, 137–8 |
automated variable selection 200–2 |
confounders 81 |
|
goodness-of-fit 196–7, 203 |
β see type II errors |
hypothesis tests 158 |
backwards elimination 202–3 |
agreement 181–6 |
backwards selection 201 |
association 186 |
bar charts 31–5, 41, 44–7 |
Bland-Altman charts 185–6 |
beneficial risk factors 105 |
Cohen’s kappa 182–4 |
bimodal distribution 47 |
continuous data 184–6 |
binary data 153, 214–15 |
limits 185–6 |
binomial distribution 48, 116 |
ordinal data 184 |
Bland-Altman charts 185–6 |
weighted kappa 184 |
blinding 86 |
analysis of variance (ANOVA) 209–11 |
block randomisation 85 |
APACHE II scores 33–4 |
boxplots 41, 61–2, 63 |
Apgar scores 25–6, 38, 121, 128, 148, |
British Regional Heart Study 36 |
174 |
|
arithmetic mean see mean |
case-control studies 11 |
ARR see absolute risk reduction |
association 177 |
assessment bias 86 |
confidence intervals 137 |
association 171–80 |
hypothesis tests 146, 153, 158 |
agreement 186 |
matched 81, 82, 102 |
confidence intervals 179 |
odds ratios 105–6 |
correlation coefficients 175–80, |
probability 98 |
183 |
risk 102–3 |
definition 171–2 |
study design 80–3 |
linear 172–3, 175 |
unmatched 81–2 |
linear regression 190–1, 192 |
case-series studies 76 |
negative 172–3 |
categorical data 4–7, 10 |
non-linear 173, 175 |
agreement 184 |
p values 176–9 |
association 180 |
positive 172–3 |
charts 30–4, 37–8, 40–1 |
|
|
Medical Statistics from Scratch Second Edition |
David Bowers |
C 2008 John Wiley & Sons, Ltd |
|
278 |
INDEX |
categorical data (Continued) confidence intervals 127, 131 frequency tables 18–20, 23–6 hypothesis tests 145, 151, 161–8 linear regression 199–200
numeric summary values 55, 57, 64 ordered 166–8
causal relationships 77, 180, 190–1 censored data 228
chance-corrected proportional agreement statistic 179, 182–4
charts 29–41
bar charts 31–5, 41 boxplots 41, 61–2, 63
categorical data 30–4, 37–8, 40–1 continuous data 35–7, 40–1 cumulative data 37–41
discrete data 34–5, 37–8, 40–1 distribution 44–7
metric data 34–8, 40–1 nominal data 30–4, 41 ogives 38–40, 41, 60–1 ordinal data 30–4, 37–8, 40–1 pie charts 30–1, 41
step charts 37–8, 41 time series charts 40–1 see also histograms
chi-squared test
hypothesis tests 145, 151, 161–8 logistic regression 221, 222 survival 234
clinical databases 240, 241 clinical trials 84
clustered bar charts 32–4 coding design 199–200 coefficient of determination 197 Cohen’s kappa 179, 182–4 cohort studies
charts 36–7
probability 100–1, 102, 104, 106–7 study design 78–80, 83
survival 238 colinearity 198 comparative studies 13
confidence intervals 111–18 agreement 183 association 179
difference between population parameters 119–31
hypothesis tests 117, 119–31, 149, 156, 163 independent populations 120–5, 127–31, 133–4
linear regression 195–6, 198 logistic regression 217
matched populations 125–6, 131 mean 112–16, 120–6, 134 median 117–18, 127–31 Minitab 120, 123, 128
Normal distribution 112–13, 120, 127
odds ratios 134–5, 137–8 proportions 116–17, 126–7
ratio of two population parameters 133–8 risk ratios 134–6
single population parameter 111–18 SPSS 120, 122–3
standard error 112–16 survival 237–8 systematic review 242–3
confounders
linear regression 202–3, 204–5 logistic regression 222
risk ratios 136 study design 81, 84
consecutive sampling 74–5 constant coefficient 191 contact sampling 74–5 contingency tables 25–6
chi-squared test 162–4 logistic regression 221 risk 104
study design 79–80, 82 continuous metric data 7–8, 10
agreement 184–6 association 176, 180 charts 35–7, 40–1 frequency tables 20–2
linear regression 193, 194, 207 numeric summary values 57, 64
control groups 84, 86 controlling for confounders 81
correlation coefficients 175–80, 183 counts 9
covariates see independent variables Cox’s regression model 236
cross-over randomised control trials 86–8 cross-section studies 12
association 177–80 study design 76–8 cross-tabulations 25–6 cumulative data 37–41
cumulative frequencies 23–4 see also ogives
|
INDEX |
279 |
data, definition 3–4 |
estimates 94–5 |
|
data collection see sampling |
see also confidence intervals |
|
databases 240, 241 |
exclusion criteria 240–1 |
|
death see survival |
expected values 163–6, 182 |
|
deciles 57 |
experimental studies 83–90 |
|
decision rules 143–4 |
explanatory variable see independent |
|
dependent variables 72, 193, 207, |
variables |
|
214–17 |
extraction of data 240–1 |
|
descriptive statistics |
|
|
charts 29–41 |
false negatives/positives 150 |
|
definition 17–18 |
Fischer’s exact test 145 |
|
distribution 43–9 |
follow-up see cohort studies |
|
frequency tables 5, 6, 17–27 |
forest plots 241–3, 250 |
|
numeric summary values 51–68 |
forwards elimination 202 |
|
design variables 199–200 |
forwards selection 201 |
|
deviance coefficient 222 |
frequency matching 81–2 |
|
diagnostics 205–9 |
frequency tables 5, 6, 17–27 |
|
discrete metric data 9, 10 |
categorical data 18–20, 23–6 |
|
charts 34–5, 37–8, 40–1 |
contingency tables 25–6 |
|
frequency tables 23 |
continuous data 20–2 |
|
numeric summary values 57, 64 |
cross-tabulations 25–6 |
|
dispersion measures 52, 57–68 |
cumulative frequencies 23–4 |
|
distribution 43–9 |
discrete data 23 |
|
bimodal 47 |
grouping data 20–2 |
|
binomial 116 |
metric data 20–3 |
|
hypothesis tests 144–5 |
nominal data 18–19 |
|
numeric summary values 55, 57, 58, |
open-ended groups 22 |
|
65–8 |
ordinal data 20, 23–4 |
|
outliers 44 |
ranking data 27 |
|
skew 44–5, 55, 57, 62, 64, 131 |
relative frequency 19–20 |
|
symmetric 44, 46 |
funnel plots 244–6 |
|
transformed data 66–8 |
|
|
uniform 43 |
GCS see Glasgow Coma Scale |
|
see also Normal distribution |
generalisation see statistical inference |
|
double-blind randomised control trials |
generalised linear model 209 |
|
86 |
Glasgow Coma Scale (GCS) 5–7, 23–4 |
|
drop-out 89 |
goodness-of-fit 196–7, 203–4, 222–3 |
|
dummy variables 199–200 |
grouped data 20–2, 35–7 |
|
|
grouped frequency distributions 21–2 |
|
Edinburgh Maternal Depression |
|
|
Scale 116 |
hazard function 236 |
|
elimination methods 202–3 |
hazard ratios 235–6 |
|
errors |
heterogeneity 246–50 |
|
blinding 86 |
histograms 35–7, 41 |
|
drop-out 89 |
confidence intervals 120 |
|
hypothesis tests 149–50 |
distribution 44–6, 56, 65, 67 |
|
linear regression 194, 207–8, |
linear regression 211 |
|
211 |
numeric summary values 56, 65, |
|
recall bias 83 |
67 |
|
sampling 73, 83, 94, 112 |
homogeneity 246–50 |
|
selection bias 83, 84–5 |
homoskedasticity 195 |
|
280 |
INDEX |
Hosmer-Lemeshow statistic 222–3 hypothesis tests
chi-squared test 145, 151, 161–8, 221, 222, 234
confidence intervals 117, 119–31, 149, 156, 163
decision rules 143–4
difference between population parameters 141–54
equality of population proportions 161–8 errors 149–50
Fischer’s exact test 145
independent populations 119–25, 127–31, 145–9, 151, 152–4, 162–3
Kruskal-Wallis test 145 logistic regression 221, 222 McNemar’s test 145, 162
Mann-Whitney rank-sums test 127–31, 145, 147–9, 151
matched populations 125–6, 131, 145, 147, 149, 151, 162
matched-pairs t test 125–6, 145, 147, 151 mean 145–7
median 145, 147–9 Minitab 146, 148–9 Normal distribution 144–5
p values 143–4, 146–9, 156–9, 164–6, 168 paired populations 145
power 150, 151–2, 168 procedure 143 proportions 161–8
ratio of two population parameters 155–9 research questions 142
rules of thumb 152–4 significance level 144, 150, 153 SPSS 146, 148
trend 166–8
two-sample t test 120–5, 145–6, 151, 222 Wilcoxon signed-rank test 117, 131, 145, 149,
151
see also null hypothesis
incidence rate 53–4 inclusion criteria 240–1 independent populations
difference 120–5, 127–31 hypothesis tests 145–9, 151, 152–4,
162–3
Mann-Whitney rank-sums test 127–31 ratios 133–4
two-sample t test 120–5
independent variables
linear regression 193, 199–201, 204, 207–8 logistic regression 216, 221–2
inferences 77, 93–5
informed guesses see confidence intervals Injury Severity Scale (ISS) 184 intention-to-treat 89
interquartile range (iqr) 58–61, 63–4, 232 interval property 8
iqr see interquartile range ISS see Injury Severity Scale
journals 244
Kaplan-Meier curves 230–1, 233–5 Kaplan-Meier tables 228–30 Kappa statistic 179, 182–4
Kendal’s rank-order correlation coefficient 180 Killip scale 157
Kruskal-Wallis test 145
L’Abbe´ plots 247
left skew see positive skew Levene’s test 123
limits of agreement 185–6 linear association 172–3, 175 linear regression 189–211
analysis of variance 209–11 association 190–1, 192 assumptions 194–5, 205–9 causal relationships 190–1 coding design 199–200 colinearity 198 confounders 202–3, 204–5 design variables 199–200 diagnostics 205–9
goodness-of-fit 196–7, 203–4 Minitab 196
model-building 200–1 multiple 197–9, 203, 205–9
nominal independent variables 199–200 ordinary least squares 193–8, 205, 209 population regression equation 194 sample regression equation 193
SPSS 195–6
statistical significance 195–6 variable selection 200–3 variation 190–1
location measures 52, 54–7, 59–61 log-log plots 238
log-rank test 233–5
|
INDEX |
281 |
logistic regression 213–23 |
logistic regression 222 |
|
binary dependent variables 214–15 |
numeric summary values 57, 64 |
|
goodness-of-fit 222–3 |
MLE see maximum likelihood estimation |
|
maximum likelihood estimation 217–18 |
mode 54, 57 |
|
Minitab 217–20 |
model-building 200–1 |
|
model-building 221–2 |
mound-shaped see symmetric distribution |
|
multiple 221 |
multi-colinearity 198 |
|
odds ratios 217, 218–19, 220 |
multiple linear regression 197–9, 203, 205–9 |
|
regression coefficient 219 |
multiple logistic regression 221 |
|
SPSS 217, 220–1 |
multivariate analysis 223, 238 |
|
statistical inference 220–1 |
|
|
longitudinal studies see case-control studies; |
n-tiles 57 |
|
cohort studies |
negative |
|
|
association 172–3 |
|
McNemar’s test 145, 162 |
outcomes 244 |
|
Mann-Whitney rank-sums test 127–31, 145, |
skew 44–5, 55, 62 |
|
147–9, 151 |
NNT see number needed to treat |
|
Mantel-Haenszel test 248–50 |
nominal categorical data 4–5, 10 |
|
manual variable selection 200, 202–3 |
agreement 184 |
|
matched case-control studies 81, 82, 102 |
charts 30–4, 41 |
|
matched populations 125–6, 131, 145, 147, 149, |
frequency tables 18–19 |
|
151, 162 |
linear regression 199–200 |
|
matched-pairs t test 125–6, 145, 147, 151 |
numeric summary values 57, 64 |
|
maximum likelihood estimation (MLE) 217–18 |
non-linear association 173, 175 |
|
mean |
see also logistic regression |
|
confidence intervals 112–16, 120–6, 134 |
non-parametric tests 127, 144–5, 151 |
|
hypothesis tests 145–7 |
Normal distribution 48–9 |
|
linear regression 197–8 |
association 176 |
|
numeric summary values 55, 57 |
confidence intervals 112–13, 120, 127 |
|
standard error 112–16 |
hypothesis tests 144–5 |
|
statistical inference 94 |
linear regression 194, 207, 209 |
|
systematic review 242–3, 249 |
probability 100 |
|
measurements 8, 10 |
standard deviation 65–8 |
|
median |
null hypothesis |
|
confidence intervals 117–18, 127–31 |
difference between population parameters |
|
hypothesis tests 145, 147–9 |
142–5, 148, 150 |
|
numeric summary values 54–5, 57, 59–61 |
ratio of two population parameters 155–6, 158, |
|
statistical inference 94 |
163–4, 168 |
|
survival time 231–2 |
survival 233–4 |
|
meta-analysis 239, 240, 246–50 |
number lines 6 |
|
homogeneity/heterogeneity 246–50 |
number needed to treat (NNT) 98, 106–7 |
|
L’Abbe´ plots 247 |
numeric summary values 51–68 |
|
Mantel-Haenszel test 248–50 |
dispersion measures 52, 57–68 |
|
metric data 4, 7–9, 10 |
distribution 55, 57, 58, 65–8 |
|
agreement 184–6 |
incidence rate 53–4 |
|
association 176, 180 |
interquartile range 58–61, 63–4 |
|
charts 34–8, 40–1 |
location measures 52, 54–7, 59–61 |
|
confidence intervals 120, 126, 127, 131 |
numbers 52–3 |
|
frequency tables 20–3 |
ogives 60–1 |
|
hypothesis tests 145, 152–3 |
outliers 55, 57, 58, 62 |
|
linear regression 193, 194, 207 |
percentages 52–3 |
|
282 |
INDEX |
numeric summary values (Continued) percentiles 56–7
prevalence 53–4 proportions 52–3 quantitation 52 range 58
skew 55, 57, 62, 64 standard deviation 62–8 transformed data 66–8
observed values 163–6 odds 101–2, 103
odds ratios 105–6
confidence intervals 134–5, 137–8 hypothesis tests 158–9
logistic regression 217, 218–19, 220 systematic review 245–6, 248–9
ogives 38–40, 41, 60–1
OLS see ordinary least squares open trials 86
open-ended groups 22 opinions 77
ordered categorical data 166–8 ordering of data 5–7, 10, 18–20 ordinal categorical data 5–7, 10
agreement 184 association 180
charts 30–4, 37–8, 40–1 confidence intervals 127, 131 frequency tables 19–20, 23–4 hypothesis tests 145
numeric summary values 55, 57, 64 ordinary least squares (OLS) 193–8, 205, 209 outcome variables see dependent variables outliers
distribution 44 frequency tables 22 meta-analysis 247
numeric summary values 55, 57, 58, 62 OXCHECK Study Group 39
pvalues association 176–9
hypothesis testing 143–4, 146–9, 156–9, 164–6, 168
linear regression 195–7, 198, 201–2 logistic regression 217, 220, 221–2 survival 234, 237–8
Palliative Care Outcome scale (POS) 183 parallel design 86
parametric tests 127, 144–5, 151
parsimony 202
Pearson’s correlation coefficient 175–7 percentages
cumulative frequency 38–40 frequency 19–20
numeric summary values 52–3 percentiles 56–7
period prevalence 53 pie charts 30–1, 41 placebo bias 86
point-biseral correlation coefficient 180 point prevalence 53
Poisson distribution 48–9 population
correlation coefficients 175–7 difference between parameters 119–31,
141–54
logistic regression model 215–16 mean 112–16, 120–6, 134, 145–7 median 117–18, 127–31, 145, 147–9 odds ratios 137, 158–9
proportions 116–17, 126–7
ratio of two parameters 133–8, 155–9 regression equation 194
risk ratios 155–6
single parameter 111–18 statistical inference 93–5 study design 72–3 survival 230
see also confidence intervals; hypothesis tests
POS see Palliative Care Outcome scale positive
association 172–3 outcomes 244
skew 44–5, 55, 57, 62 power of a test 150, 151–2, 168 predictions 196
predictors see independent variables prevalence 53–4, 77
probability 97–100 calculation 99–100
case-control studies 98, 102–3, 105–6 cohort studies 100–1, 102, 104, 106–7 definition 98
logistic regression 215 Normal distribution 100
number needed to treat 98, 106–7 odds 101–2, 103
odds ratios 105–6 Poisson distribution 48–9
INDEX |
283 |
risk 100–1, 102–3 risk ratios 104 survival 228–31
proportional frequency 99 proportional hazards 236–8 proportions
confidence intervals 116–17, 126–7 hypothesis tests 161–8
numeric summary values 52–3 populations 161–8
samples 116
prospective studies see cohort studies
Psychiatric Symptom Frequency (PSF) scale 46–7 publication bias 244, 245
quintiles 57
random number tables 85, 251 randomisation 74, 84–5, 88–9 randomised controlled trials (RCT)
hypothesis tests 146, 151, 156–7, 165 study design 85, 86–90
systematic review 242 range 58
ranked data frequency tables 27
Kendal’s rank-order correlation coefficient 180
log-rank test 233–5
Mann-Whitney rank-sums test 127–31, 145, 147–9, 151
Spearman’s rank correlation coefficient 177–80, 183
Wilcoxon signed-rank test 117, 131, 145, 149, 151
ratio property 8
RCT see randomised control trials recall bias 83
reference values 102
regression see linear regression; logistic regression relative frequency 19–20
cumulative 38–9, 60 relative risk see risk ratios research questions 142 residuals 194, 207–8, 211 response bias 86
response variables see dependent variables retrospective studies see case-control studies review see systematic review
right skew see negative skew risk 100–1, 102–3, 217
risk ratios 100, 104 confidence intervals 134–6 hypothesis tests 155–7 survival 237
systematic review 242, 245, 248, 250 rules of thumb 152–4
sample
correlation coefficients 175–80 logistic regression model 216 mean 112, 116, 120–2, 134 odds ratios 137
percentage 94 proportions 116 regression equation 193 statistic 94
survival 230 sampling 72, 73
errors 73, 83, 94, 112 frames 74
randomisation 74, 84–5, 88–9 statistical inference 93–5 types 74–5
scatterplots 172–5, 176
linear regression 192, 196, 201, 208–11 logistic regression 214–16
selection bias 83, 84–5, 88–9 significance level (α) 144, 150, 153 simple bar charts 31–2
simple random sampling 74 skew 44–5, 55, 57, 62, 64, 131 slope coefficient 191
Spearman’s rank correlation coefficient 177–80, 183
spread see dispersion measures stacked bar charts 34 standard deviation 62–8
agreement 185–6 confidence intervals 120, 123
standard error 112–16 statistical inference 77, 93–5 step charts 37–8, 41 stepwise selection 201–2
straight line models see linear regression stratified random sampling 74
study design 71–90 blinding 86
case-control studies 80–3 case-series studies 76 clinical trials 84
cohort studies 78–80, 83
284 |
INDEX |
study design (Continued) |
Mantel-Haenszel test 248–50 |
confounders 81, 84 |
meta-analysis 239, 240, 246–50 |
contingency tables 79–80, 82 |
methods 240–3 |
cross-section studies 76–8 |
publication bias 244, 245 |
experimental studies 83–90 |
search strategy 241 |
intention-to-treat 89 |
|
matching 81–2 |
t distribution 114, 120–6, 145–7, 151, 222 |
outcome variables 72 |
tables see frequency tables |
populations 72–3 |
target populations 73, 75, 93–4 |
randomisation 83, 84–5, 88–9 |
test statistic 164 |
randomised control trials 85, 86–90 |
tests see hypothesis tests |
sampling 72–5, 83–5, 88–9 |
time series charts 40–1 |
types of study 75–81 |
transformed data 66–8 |
study populations 73, 75, 93–4 |
treatment bias 86 |
sub-groups 25 |
treatment groups 84, 86 |
sum of squares 63 |
trend 166–8 |
summary values see numeric summary values |
two-sample t test 120–5, 145–6, 151, 222 |
surveys 76–8 |
type I/II errors 150 |
survival 227–38 |
|
censored data 228 |
uniform distributions 43 |
comparison between groups 232–9 |
units 5, 7–9 |
Cox’s regression model 236 |
univariate analysis 238 |
hazard ratios 235–6 |
univariate logistic regression 222 |
Kaplan-Meier curves 230–1, 233–5 |
unmatched case-control studies 81–2 |
Kaplan-Meier tables 228–30 |
|
log-log plots 238 |
variables |
log-rank test 233–5 |
characteristics 9–13 |
median 231–2 |
definition 3–4 |
null hypothesis 233–4 |
selection 200–3 |
probability 228–31 |
types 4–9 |
proportional hazards 236–8 |
see also categorical; continuous; discrete; |
single groups 228 |
metric; nominal; ordinal data |
symmetric distribution 44, 46 |
variation 190–1 |
systematic random sampling 74 |
visual analogue scale (VAS) 10, 59, 118 |
systematic review 239–45 |
|
extraction of data 240–1 |
Wald statistic 220–1 |
forest plots 241–3, 250 |
weighted kappa 184 |
funnel plots 244–6 |
weighted mean 242–3, 249 |
homogeneity/heterogeneity 246–50 |
Wilcoxon signed-rank test 117, 131, 145, 149, |
identification of trials 240–1 |
151 |
inclusion criteria 240–1 |
|
L’Abbe´ plots 247 |
z distribution 220 |
