Statistics for clinical research An introductory course.
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Transcript of Statistics for clinical research An introductory course.
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Statistics for clinical Statistics for clinical researchresearch
An introductory courseAn introductory course
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Session 2Session 2
Comparing two groupsComparing two groups
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Previous sessionPrevious session
Normal distributionNormal distribution
Standard Deviation (of measurements)Standard Deviation (of measurements)
Standard Error (of the mean)Standard Error (of the mean)
Confidence Interval of measurementsConfidence Interval of measurements
Confidence Interval of the meanConfidence Interval of the mean
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Main overviewMain overview
Dealing with both Dealing with both MeansMeans and and ProportionsProportions
TwoTwo groups will be compared groups will be compared
Effect SizeEffect Size along with its along with its Confidence Confidence IntervalInterval (C.I.)(C.I.) will be calculated from data will be calculated from data
Remember theRemember the C.I. C.I. tells us about the tells us about the uncertaintyuncertainty of the of the effect sizeeffect size
The different calculations for effect sizesThe different calculations for effect sizes
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MeansMeans
Means calculated from measured dataMeans calculated from measured data
Standard Deviation (of Measurements)Standard Deviation (of Measurements)
Standard Error (of the Mean)Standard Error (of the Mean)
Effect Size Effect Size == Difference in MeansDifference in Means
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ProportionsProportions ProportionProportion
Binary outcome (e.g. yes/no)Binary outcome (e.g. yes/no) Number between 0 and 1Number between 0 and 1
2x2 table2x2 table
Effect sizesEffect sizes Risk Difference (RD); Relative Risk (RR); Risk Difference (RD); Relative Risk (RR);
Odds Ratio (OR)Odds Ratio (OR)
Group 1Group 1 Group 2Group 2
PositivePositive pp11 pp22
NegativeNegative nn11 nn22
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Comparing two groupsComparing two groupsTwo proportionsTwo proportions
Risk DifferenceRisk Difference Number Needed to TreatNumber Needed to Treat Relative RiskRelative Risk Odds RatioOdds Ratio Fisher’s Exact ProbabilityFisher’s Exact Probability
Two meansTwo means The The tt-distribution-distribution Difference between meansDifference between means
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Risk DifferenceRisk Difference Risk is a proportion (number between 0 Risk is a proportion (number between 0
and 1)and 1) Each group incorporate its own riskEach group incorporate its own risk Group 1: 15 people are given money…Group 1: 15 people are given money…
Happy Happy = 12= 12Not happy Not happy = 3= 3Total Total = 15= 15Risk of happiness = 12/15 = 0.8Risk of happiness = 12/15 = 0.8
Group 2: 10 people are not given money…Group 2: 10 people are not given money…Happy Happy = 5= 5Not happy Not happy = 5= 5Total Total = 10= 10Risk of happiness = 5/10 = 0.5Risk of happiness = 5/10 = 0.5
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Risk DifferenceRisk Difference
Risk Difference (RD) is the risk of Risk Difference (RD) is the risk of one group subtracted from the risk one group subtracted from the risk of the other groupof the other group
RD = 0.8 – 0.5 = 0.3RD = 0.8 – 0.5 = 0.3
Excel file “TwoGroups.xls”Excel file “TwoGroups.xls”
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Comparing two groupsComparing two groups
Two proportionsTwo proportions Risk DifferenceRisk Difference Number Needed to TreatNumber Needed to Treat Relative RiskRelative Risk Odds RatioOdds Ratio Fisher’s Exact ProbabilityFisher’s Exact Probability
Two meansTwo means The The tt-distribution-distribution Difference between meansDifference between means
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Number Needed to TreatNumber Needed to Treat
NNT = 1 / Risk DifferenceNNT = 1 / Risk Difference
If RD = 0.21 (21%), then need to treat If RD = 0.21 (21%), then need to treat 100 to prevent 21 adverse events100 to prevent 21 adverse events
NNT = 1 / 0.21 = 5 (rounded up)NNT = 1 / 0.21 = 5 (rounded up)
5 need to be treated to prevent 1 5 need to be treated to prevent 1 additional adverse eventadditional adverse event
Excel file “TwoGroups.xls” Excel file “TwoGroups.xls”
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Comparing two groupsComparing two groups
Two proportionsTwo proportions Risk DifferenceRisk Difference Number Needed to TreatNumber Needed to Treat Relative RiskRelative Risk Odds RatioOdds Ratio Fisher’s Exact ProbabilityFisher’s Exact Probability
Two meansTwo means The The tt-distribution-distribution Difference between meansDifference between means
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Relative Risk (RR)Relative Risk (RR) Risk is a proportionRisk is a proportion
Each of the two groups has its own riskEach of the two groups has its own risk
Relative Risk (RR) is the ratio of two risksRelative Risk (RR) is the ratio of two risks
RR is mostly used for cohort studiesRR is mostly used for cohort studies
Ratios do not have a Normal distributionRatios do not have a Normal distribution
log(RR) has a Normal distributionlog(RR) has a Normal distribution
Confidence interval calculations require a Confidence interval calculations require a Normal distributionNormal distribution
Excel file “TwoGroups.xls”Excel file “TwoGroups.xls”
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Relative Risk (RR)Relative Risk (RR)
If Confidence Interval…If Confidence Interval…
Contains 1:Contains 1: No difference in No difference in outcome between two groupsoutcome between two groups
<1:<1: Less risk in group 1 Less risk in group 1
>1:>1: Greater risk in group 1 Greater risk in group 1
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Comparing two groupsComparing two groups
Two proportionsTwo proportions Risk DifferenceRisk Difference Number Needed to TreatNumber Needed to Treat Relative RiskRelative Risk Odds RatioOdds Ratio Fisher’s Exact ProbabilityFisher’s Exact Probability
Two meansTwo means The The tt-distribution-distribution Difference between meansDifference between means
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Odds Ratio (OR)Odds Ratio (OR) Odds – the number who have an event Odds – the number who have an event
divided by the number who do notdivided by the number who do not Odds of an event occurring is obtained for Odds of an event occurring is obtained for
both groupsboth groups OR mostly used for case-control studiesOR mostly used for case-control studies Ratios are not Normally distributedRatios are not Normally distributed log(OR) has a Normal distributionlog(OR) has a Normal distribution Confidence Interval calculations require a Confidence Interval calculations require a
Normal distributionNormal distribution Extra: Logistic regression is typically used to Extra: Logistic regression is typically used to
adjust odds ratios to control for potential adjust odds ratios to control for potential confounding by other variablesconfounding by other variables
Excel file “TwoGroups.xls”Excel file “TwoGroups.xls”
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Odds Ratio (OR)Odds Ratio (OR)
If Confidence Interval…If Confidence Interval…
Contains 1:Contains 1: No difference in No difference in outcome between two groupsoutcome between two groups
<1:<1: Odds in group 1 significantly Odds in group 1 significantly lessless
>1:>1: Odds in group 1 significantly Odds in group 1 significantly greatergreater
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Comparing two groupsComparing two groups
Two proportionsTwo proportions Risk DifferenceRisk Difference Number Needed to TreatNumber Needed to Treat Relative RiskRelative Risk Odds RatioOdds Ratio Fisher’s Exact ProbabilityFisher’s Exact Probability
Two meansTwo means The The tt-distribution-distribution Difference between meansDifference between means
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Fisher’s Exact TestFisher’s Exact Test
Determines if significant associations Determines if significant associations exist between group and outcomeexist between group and outcome
Used when sample sizes are smallUsed when sample sizes are small i.e. cell count < 5 in a 2x2 tablei.e. cell count < 5 in a 2x2 table
Alternative to the Chi-Square testAlternative to the Chi-Square test
Test only provides a p-value (no C.I.)Test only provides a p-value (no C.I.)
Probability of observing a result more Probability of observing a result more extreme than that observedextreme than that observed
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Comparing two groupsComparing two groups
Two proportionsTwo proportions Risk DifferenceRisk Difference Number Needed to TreatNumber Needed to Treat Relative RiskRelative Risk Odds RatioOdds Ratio Fisher’s Exact ProbabilityFisher’s Exact Probability
Two meansTwo means The The tt-distribution-distribution Difference between meansDifference between means
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The The tt-distribution-distribution
Population SD is unknown and Population SD is unknown and is estimated from the datais estimated from the data
Blue curve = Normal Blue curve = Normal distributiondistribution
Green = Green = tt-distribution with 1 -distribution with 1 degree of freedom (df)degree of freedom (df)
Red = Red = tt-distribution, 2 df-distribution, 2 df
Underlying theory of the Underlying theory of the tt-test-test
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Comparing two groupsComparing two groups
Two proportionsTwo proportions Risk DifferenceRisk Difference Number Needed to TreatNumber Needed to Treat Relative RiskRelative Risk Odds RatioOdds Ratio Fisher’s Exact ProbabilityFisher’s Exact Probability
Two meansTwo means The The tt-distribution-distribution Difference between meansDifference between means
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Difference between meansDifference between means
Two sampleTwo sample t t-test is used to test the -test is used to test the difference between two meansdifference between two means
Measurements must be considered Measurements must be considered Normally distributedNormally distributed
Quite powerful. A decision can be Quite powerful. A decision can be made with a small sample size…much made with a small sample size…much smaller than when compared to smaller than when compared to proportionsproportions
Excel file “TwoGroups.xls”Excel file “TwoGroups.xls”
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Forest PlotForest Plot
Plot effect sizes with confidence intervalsPlot effect sizes with confidence intervals
Useful in comparing multiple effect sizesUseful in comparing multiple effect sizes
Go to applet on website:Go to applet on website:
http://www.materrsc.org/Course/CI_Diff.htmlhttp://www.materrsc.org/Course/CI_Diff.html
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Additional topicsAdditional topics
Normality tests (e.g. Shapiro-Wilk)Normality tests (e.g. Shapiro-Wilk)
Test for equality of variances (e.g. Test for equality of variances (e.g. Bartlett’s test)Bartlett’s test)
tt-test for unequal variances-test for unequal variances
Paired t-test for dependent samplesPaired t-test for dependent samples
Comparing more than two groups Comparing more than two groups (e.g. one-way ANOVA)(e.g. one-way ANOVA)
Nonparametric testsNonparametric tests