Odds Ratio, Relative Risk, Absolute Risk Reduction, and the Number Needed to Treat—Which of These Should We Use?

AbstractIntroductionStatistical analyses of data and making sense of medical data have received much attention in the medical literature, but nevertheless have caused confusion among practitioners. Each researcher provides a different method for comparing treatments. For example, when the end point is binary, such as disease versus no disease, the common measures are odds ratios, relative risk, relative risk reduction, absolute risk reduction, and the number needed to treat. The question faced by the practitioner is then: Which one will help me in choosing the best treatment for my patient?MethodsThe purpose of this paper is to illustrate, using examples, how each measure is used, what it means, and what are its advantages and disadvantages.ResultsSome pairs of measures present equivalent information. Furthermore, it is shown that different measures result in different impressions.ConclusionIt is recommended that researchers report both a relative and an absolute measure and present these with appropriate confidence intervals

Visuo-Motor Coordination Deficits and Motor Impairments in Parkinson's Disease

BACKGROUND: Visuo-motor coordination (VMC) requires normal cognitive executive functionality, an ability to transform visual inputs into movement plans and motor-execution skills, all of which are known to be impaired in Parkinson's disease (PD). Not surprisingly, a VMC deficit in PD is well documented. Still, it is not known how this deficit relates to motor symptoms that are assessed routinely in the neurological clinic. Such relationship should reveal how particular motor dysfunctions combine with cognitive and sensory-motor impairments to produce a complex behavioral disability. METHODS AND FINDINGS: Thirty nine early/moderate PD patients were routinely evaluated, including motor Unified Parkinson's Disease Rating Scale (UPDRS) based assessment, A VMC testing battery in which the subjects had to track a target moving on screen along 3 different paths, and to freely trace these paths followed. Detailed kinematic analysis of tracking/tracing performance was done. Statistical analysis of the correlations between measures depicting various aspects of VMC control and UPDRS items was performed. The VMC measures which correlated most strongly with clinical symptoms represent the ability to organize tracking movements and program their direction, rather than measures representing motor-execution skills of the hand. The strong correlations of these VMC measures with total UPDRS score were weakened when the UPDRS hand-motor part was considered specifically, and were insignificant in relation to tremor of the hand. In contrast, all correlations of VMC measures with the gait/posture part of the UPDRS were found to be strongest. CONCLUSIONS: Our apparently counterintuitive findings suggest that the VMC deficit pertains more strongly to a PD related change in cognitive-executive control, than to a reduction in motor capabilities. The recently demonstrated relationship between gait/posture impairment and a cognitive decline, as found in PD, concords with this suggestion and may explain the strong correlation between VMC dysfunction and gait/posture impairment. Accordingly, we propose that what appears to reflect a motor deficit in fact represents a multisystem failure, dominated by a cognitive decline

Using Analysis of Gini (ANoGi) for Detecting Whether Two Sub-Samples Represent the Same Universe: The SOEP Experience

A particular shortcoming of panel surveys is potential bias arising from selective attrition. Based on data from the German Socio-Economic Panel Study (SOEP) we analyze potential artifacts (level, structure, inequality of income) by comparing results from two independently drawn panel sub-samples, started in 1984 and 2000, respectively. Both sub-samples carried on using the same set of follow-up rules. We apply ANOGI (ANalysis Of GIni) techniques, the equivalent of ANOVA (ANalysis Of VAriance) performed on the basis of the Gini coefficient. The decomposition followed is presented in Yitzhaki (1994). We rearrange, reinterpret and use the decomposition in the comparison of sub-populations from which the different subsamples were drawn. Taking into account indicators for income, and for control purposes those for education and satisfaction as well, significant differences between these two subsamples with respect to (income) inequality are found in the first year, which start to fade away in wave 2 and disappear in wave 3. We find credible indication for these differences to be driven by changes in response behavior of short term panel members rather than by attrition among members of the longer running sub-sample

Using Analysis of Gini (ANOGI) for Detecting Whether Two Subsamples Represent the Same Universe: The German Socio-Economic Panel Study (SOEP) Experience

A wildly discussed shortcoming of panel surveys is a potential bias arising from selective attrition. Based on data of the German Socio-Economic Panel Study (SOEP), the authors analyze potential artifacts (level, structure, income inequality) by comparing results for two independently drawn panel subsamples started in 1984 and 2000. They apply ANOGI (analysis of Gini) techniques, the equivalent of ANOVA performed with the Gini coefficient. They rearrange, reinterpret, and use the decomposition in the comparison of subpopulations from which the different samples were drawn. Taking into account indicators for income, significant differences between these two samples with respect to income inequality are found in the first year, which start to fade away in Wave 2 and disappear in Wave 3. The authors find credible indication for these differences to be driven by changes in response behavior of short-term panel members rather than by attrition among members of the longer running sample.Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich. - This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively

Education effects on cognitive function in a healthy aged Arab population

Abstract Background-The Minimental State Examination (MMSE) has not been validated in Arabic speaking populations. The Brookdale Cognitive Screening Test (BCST) has been developed for use in low schooling populations. We investigated the influence of gender, education and occupation in a cognitively normal community sample assessed with an Arabic translation of the MMSE and the BCST

Efficacy and moderators of efficacy of cognitive behavioural therapies with a trauma focus in children and adolescents: an individual participant data meta-analysis of randomised trials

Background: Existing clinical trials of cognitive behavioural therapies with a trauma focus (CBTs-TF) are underpowered to examine key variables that might moderate treatment effects. We aimed to determine the efficacy of CBTs-TF for young people, relative to passive and active control conditions, and elucidate putative individual-level and treatment-level moderators. Methods: This was an individual participant data meta-analysis of published and unpublished randomised studies in young people aged 6-18 years exposed to trauma. We included studies identified by the latest UK National Institute of Health and Care Excellence guidelines (completed on Jan 29, 2018) and updated their search. The search strategy included database searches restricted to publications between Jan 1, 2018, and Nov 12, 2019; grey literature search of trial registries ClinicalTrials.gov and ISRCTN; preprint archives PsyArXiv and bioRxiv; and use of social media and emails to key authors to identify any unpublished datasets. The primary outcome was post-traumatic stress symptoms after treatment (<1 month after the final session). Predominantly, one-stage random-effects models were fitted. This study is registered with PROSPERO, CRD42019151954. Findings: We identified 38 studies; 25 studies provided individual participant data, comprising 1686 young people (mean age 13·65 years [SD 3·01]), with 802 receiving CBTs-TF and 884 a control condition. The risk-of-bias assessment indicated five studies as low risk and 20 studies with some concerns. Participants who received CBTs-TF had lower mean post-traumatic stress symptoms after treatment than those who received the control conditions, after adjusting for post-traumatic stress symptoms before treatment (b=-13·17, 95% CI -17·84 to -8·50, p<0·001, τ2=103·72). Moderation analysis indicated that this effect of CBTs-TF on post-traumatic stress symptoms post-treatment increased by 0·15 units (b=-0·15, 95% CI -0·29 to -0·01, p=0·041, τ2=0·03) for each unit increase in pre-treatment post-traumatic stress symptoms. Interpretation: This is the first individual participant data meta-analysis of young people exposed to trauma. Our findings support CBTs-TF as the first-line treatment, irrespective of age, gender, trauma characteristics, or carer involvement in treatment, with particular benefits for those with higher initial distress

Correlation and the time interval over which the variables are measured - A non-parametric approach.

It is known that when one (or both) variable is multiplicative, the choice of differencing intervals (n) (for example, differencing interval of n = 7 means a weekly datum which is the product of seven daily data) affects the Pearson correlation coefficient (ρ) between variables (often asset returns) and that ρ converges to zero as n increases. This fact can cause the resulting correlation to be arbitrary, hence unreliable. We suggest using Spearman correlation (r) and prove that as n increases Spearman correlation tends to a limit which only depends on Pearson correlation based on the original data (i.e., the value for a single period). In addition, we show, via simulation, that the relative variability (CV) of the estimator of ρ increases with n and that r does not share this disadvantage. Therefore, we suggest using Spearman when one (or both) variable is multiplicative

A Measure of Association Based on Gini's Mean Difference

A measure of association between two random variables is proposed, which represents a compromise between the classical correlation coefficient and the rank correlation coefficient. The new measure is based on the covariance between two variables where one variable is taken in its variate values while the other is ranked. The large sample distribution of this measure is studied and some possible applications are mentioned