Looking for Validity or Testing It? The Perils of Stepwise Regression, Extreme-Scores Analysis, Heteroscedasticity, and Measurement Error

When researchers introduce a new test they have to demonstrate that it is valid, using unbiased designs and suitable statistical procedures. In this article we use Monte Carlo analyses to highlight how incorrect statistical procedures (i.e., stepwise regression, extreme scores analyses) or ignoring regression assumptions (e.g., heteroscedasticity) contribute to wrong validity estimates. Beyond these demonstrations, and as an example, we re-examined the results reported by Warwick, Nettelbeck, and Ward (2010) concerning the validity of the Ability Emotional Intelligence Measure (AEIM). Warwick et al. used the wrong statistical procedures to conclude that the AEIM was incrementally valid beyond intelligence and personality traits in predicting various outcomes. In our re-analysis, we found that the reliability-corrected multiple correlation of their measures with personality and intelligence was up to .69. Using robust statistical procedures and appropriate controls, we also found that the AEIM did not predict incremental variance in GPA, stress, loneliness, or well-being, demonstrating the importance for testing validity instead of looking for it.

Adapting football to the child: an application of the logistic regression model in observational mewthodology.

Logistic regression is included into the analysis techniques which are valid for observationalmethodology. However, its presence at the heart of thismethodology, and more specifically in physical activity and sports studies, is scarce. With a view to highlighting the possibilities this technique offers within the scope of observational methodology applied to physical activity and sports, an application of the logistic regression model is presented. The model is applied in the context of an observational design which aims to determine, from the analysis of use of the playing area, which football discipline (7 a side football, 9 a side football or 11 a side football) is best adapted to the child"s possibilities. A multiple logistic regression model can provide an effective prognosis regarding the probability of a move being successful (reaching the opposing goal area) depending on the sector in which the move commenced and the football discipline which is being played.

Ensemble methods for environmental data modelling with support vector regression

This paper investigates the use of ensemble of predictors in order to improve the performance of spatial prediction methods. Support vector regression (SVR), a popular method from the field of statistical machine learning, is used. Several instances of SVR are combined using different data sampling schemes (bagging and boosting). Bagging shows good performance, and proves to be more computationally efficient than training a single SVR model while reducing error. Boosting, however, does not improve results on this specific problem.

Evaluation of a multicomponent worksite health promotion program for cardiovascular risk factors-correcting for the regression towards the mean effect.

BACKGROUND: We assessed the impact of a multicomponent worksite health promotion program for0 reducing cardiovascular risk factors (CVRF) with short intervention, adjusting for regression towards the mean (RTM) affecting such nonexperimental study without control group. METHODS: A cohort of 4,198 workers (aged 42 +/- 10 years, range 16-76 years, 27% women) were analyzed at 3.7-year interval and stratified by each CVRF risk category (low/medium/high blood pressure [BP], total cholesterol [TC], body mass index [BMI], and smoking) with RTM and secular trend adjustments. Intervention consisted of 15 min CVRF screening and individualized counseling by health professionals to medium- and high-risk individuals, with eventual physician referral. RESULTS: High-risk groups participants improved diastolic BP (-3.4 mm Hg [95%CI: -5.1, -1.7]) in 190 hypertensive patients, TC (-0.58 mmol/l [-0.71, -0.44]) in 693 hypercholesterolemic patients, and smoking (-3.1 cig/day [-3.9, -2.3]) in 808 smokers, while systolic BP changes reflected RTM. Low-risk individuals without counseling deteriorated TC and BMI. Body weight increased uniformly in all risk groups (+0.35 kg/year). CONCLUSIONS: In real-world conditions, short intervention program participants in high-risk groups for diastolic BP, TC, and smoking improved their CVRF, whereas low-risk TC and BMI groups deteriorated. Future programs may include specific advises to low-risk groups to maintain a favorable CVRF profile.

Aplicació en línia d'un sistema variable de control multivariable en un Reactor ..

L’objecte del present treball és la realització d’una aplicació que permeti portar a terme el control estadístic multivariable en línia d’una planta SBR.Aquesta eina ha de permetre realitzar un anàlisi estadístic multivariable complet del lot en procés, de l’últim lot finalitzat i de la resta de lots processats a la planta.L’aplicació s’ha de realitzar en l’entorn LabVIEW. L’elecció d’aquest programa vecondicionada per l’actualització del mòdul de monitorització de la planta que s’estàdesenvolupant en aquest mateix entorn

Modifying effect of dual antiplatelet therapy on incidence of stent thrombosis according to implanted drug-eluting stent type.

AIM: To investigate the putative modifying effect of dual antiplatelet therapy (DAPT) use on the incidence of stent thrombosis at 3 years in patients randomized to Endeavor zotarolimus-eluting stent (E-ZES) or Cypher sirolimus-eluting stent (C-SES). METHODS AND RESULTS: Of 8709 patients in PROTECT, 4357 were randomized to E-ZES and 4352 to C-SES. Aspirin was to be given indefinitely, and clopidogrel/ticlopidine for ≥3 months or up to 12 months after implantation. Main outcome measures were definite or probable stent thrombosis at 3 years. Multivariable Cox regression analysis was applied, with stent type, DAPT, and their interaction as the main outcome determinants. Dual antiplatelet therapy adherence remained the same in the E-ZES and C-SES groups (79.6% at 1 year, 32.8% at 2 years, and 21.6% at 3 years). We observed a statistically significant (P = 0.0052) heterogeneity in treatment effect of stent type in relation to DAPT. In the absence of DAPT, stent thrombosis was lower with E-ZES  vs. C-SES (adjusted hazard ratio 0.38, 95% confidence interval 0.19, 0.75; P = 0.0056). In the presence of DAPT, no difference was found (1.18; 0.79, 1.77; P = 0.43). CONCLUSION: A strong interaction was observed between drug-eluting stent type and DAPT use, most likely prompted by the vascular healing response induced by the implanted DES system. These results suggest that the incidence of stent thrombosis in DES trials should not be evaluated independently of DAPT use, and the optimal duration of DAPT will likely depend upon stent type (Clinicaltrials.gov number NCT00476957).

Reference values and factors associated with renal resistive index in a family-based population study.

Increased renal resistive index (RRI) has been recently associated with target organ damage and cardiovascular or renal outcomes in patients with hypertension and diabetes mellitus. However, reference values in the general population and information on familial aggregation are largely lacking. We determined the distribution of RRI, associated factors, and heritability in a population-based study. Families of European ancestry were randomly selected in 3 Swiss cities. Anthropometric parameters and cardiovascular risk factors were assessed. A renal Doppler ultrasound was performed, and RRI was measured in 3 segmental arteries of both kidneys. We used multilevel linear regression analysis to explore the factors associated with RRI, adjusting for center and family relationships. Sex-specific reference values for RRI were generated according to age. Heritability was estimated by variance components using the ASSOC program (SAGE software). Four hundred women (mean age±SD, 44.9±16.7 years) and 326 men (42.1±16.8 years) with normal renal ultrasound had mean RRI of 0.64±0.05 and 0.62±0.05, respectively (P<0.001). In multivariable analyses, RRI was positively associated with female sex, age, systolic blood pressure, and body mass index. We observed an inverse correlation with diastolic blood pressure and heart rate. Age had a nonlinear association with RRI. We found no independent association of RRI with diabetes mellitus, hypertension treatment, smoking, cholesterol levels, or estimated glomerular filtration rate. The adjusted heritability estimate was 42±8% (P<0.001). In a population-based sample with normal renal ultrasound, RRI normal values depend on sex, age, blood pressure, heart rate, and body mass index. The significant heritability of RRI suggests that genes influence this phenotype.

Comparisons of Estimates of Annual Exceedance-Probability Discharges for Small Drainage Basins in Iowa, Based on Data through Water Year 2013, TR-678, 2015

Traditionally, the Iowa Department of Transportation has used the Iowa Runoff Chart and single-variable regional-regression equations (RREs) from a U.S. Geological Survey report (published in 1987) as the primary methods to estimate annual exceedance-probability discharge (AEPD) for small (20 square miles or less) drainage basins in Iowa. With the publication of new multi- and single-variable RREs by the U.S. Geological Survey (published in 2013), the Iowa Department of Transportation needs to determine which methods of AEPD estimation provide the best accuracy and the least bias for small drainage basins in Iowa. Twenty five streamgages with drainage areas less than 2 square miles (mi2) and 55 streamgages with drainage areas between 2 and 20 mi2 were selected for the comparisons that used two evaluation metrics. Estimates of AEPDs calculated for the streamgages using the expected moments algorithm/multiple Grubbs-Beck test analysis method were compared to estimates of AEPDs calculated from the 2013 multivariable RREs; the 2013 single-variable RREs; the 1987 single-variable RREs; the TR-55 rainfall-runoff model; and the Iowa Runoff Chart. For the 25 streamgages with drainage areas less than 2 mi2, results of the comparisons seem to indicate the best overall accuracy and the least bias may be achieved by using the TR-55 method for flood regions 1 and 3 (published in 2013) and by using the 1987 single-variable RREs for flood region 2 (published in 2013). For drainage basins with areas between 2 and 20 mi2, results of the comparisons seem to indicate the best overall accuracy and the least bias may be achieved by using the 1987 single-variable RREs for the Southern Iowa Drift Plain landform region and for flood region 3 (published in 2013), by using the 2013 multivariable RREs for the Iowan Surface landform region, and by using the 2013 or 1987 single-variable RREs for flood region 2 (published in 2013). For all other landform or flood regions in Iowa, use of the 2013 single-variable RREs may provide the best overall accuracy and the least bias. An examination was conducted to understand why the 1987 single-variable RREs seem to provide better accuracy and less bias than either of the 2013 multi- or single-variable RREs. A comparison of 1-percent annual exceedance-probability regression lines for hydrologic regions 1–4 from the 1987 single-variable RREs and for flood regions 1–3 from the 2013 single-variable RREs indicates that the 1987 single-variable regional-regression lines generally have steeper slopes and lower discharges when compared to 2013 single-variable regional-regression lines for corresponding areas of Iowa. The combination of the definition of hydrologic regions, the lower discharges, and the steeper slopes of regression lines associated with the 1987 single-variable RREs seem to provide better accuracy and less bias when compared to the 2013 multi- or single-variable RREs; better accuracy and less bias was determined particularly for drainage areas less than 2 mi2, and also for some drainage areas between 2 and 20 mi2. The 2013 multi- and single-variable RREs are considered to provide better accuracy and less bias for larger drainage areas. Results of this study indicate that additional research is needed to address the curvilinear relation between drainage area and AEPDs for areas of Iowa.

Physical performance limitations in adolescent and adult survivors of childhood cancer and their siblings.

PURPOSE: This study investigates physical performance limitations for sports and daily activities in recently diagnosed childhood cancer survivors and siblings. METHODS: The Swiss Childhood Cancer Survivor Study sent a questionnaire to all survivors (≥ 16 years) registered in the Swiss Childhood Cancer Registry, who survived >5 years and were diagnosed 1976-2003 aged <16 years. Siblings received similar questionnaires. We assessed two types of physical performance limitations: 1) limitations in sports; 2) limitations in daily activities (using SF-36 physical function score). We compared results between survivors diagnosed before and after 1990 and determined predictors for both types of limitations by multivariable logistic regression. RESULTS: The sample included 1038 survivors and 534 siblings. Overall, 96 survivors (9.5%) and 7 siblings (1.1%) reported a limitation in sports (Odds ratio 5.5, 95%CI 2.9-10.4, p<0.001), mainly caused by musculoskeletal and neurological problems. Findings were even more pronounced for children diagnosed more recently (OR 4.8, CI 2.4-9.6 and 8.3, CI 3.7-18.8 for those diagnosed <1990 and ≥ 1990, respectively; p=0.025). Mean physical function score for limitations in daily activities was 49.6 (CI 48.9-50.4) in survivors and 53.1 (CI 52.5-53.7) in siblings (p<0.001). Again, differences tended to be larger in children diagnosed more recently. Survivors of bone tumors, CNS tumors and retinoblastoma and children treated with radiotherapy were most strongly affected. CONCLUSION: Survivors of childhood cancer, even those diagnosed recently and treated with modern protocols, remain at high risk for physical performance limitations. Treatment and follow-up care should include tailored interventions to mitigate these late effects in high-risk patients.

The T309G Murine Double Minute 2 Gene Polymorphism Is an Independent Prognostic Factor for Patients with Renal Cell Carcinoma.

The purpose of this study was to evaluate the association of the T309G MDM2 gene polymorphism with renal cell carcinoma (RCC) risk, pathology, and cancer-specific survival (CSS). T309G MDM2 was genotyped in 449 Caucasians, including 240 with RCC and 209 cancer-free controls. The T309G MDM2 genotype was TT in 174 (38.8%), GT in 214 (47.7%), and GG in 61 (13.6%) subjects, without any significant differences between cases and controls on both univariable (p=0.58) and multivariable logistic regression (each p>0.25). Furthermore, T309G MDM2 was not linked with T stage (p=0.75), N stage (p=0.37), M stage (p=0.94), grade (p=0.21), and subtype (p=0.55). There was, however, a statistically significant association of T309G MDM2 with CSS (p=0.022): patients with TT had significantly worse survival than GG/GT (p=0.009), while those with GT and GG had similar outcomes (p=0.92). The 5-year survival rate for patients with TT, GT, and GG was 69.5%, 84.5%, and 89.7%, respectively. On the multivariable analysis, T309G was identified as an independent prognostic factor. The T309G MDM2 polymorphism is an independent prognostic factor for patients with RCC, with the TT genotype being associated with worse prognosis. In this study, there were no significant associations with RCC risk and pathology.

Childhood epilepsy with neuropsychological regression and continuous spike waves during sleep: epilepsy surgery in a young adult.

We describe the case of a man with a history of complex partial seizures and severe language, cognitive and behavioural regression during early childhood (3.5 years), who underwent epilepsy surgery at the age of 25 years. His early epilepsy had clinical and electroencephalogram features of the syndromes of epilepsy with continuous spike waves during sleep and acquired epileptic aphasia (Landau-Kleffner syndrome), which we considered initially to be of idiopathic origin. Seizures recurred at 19 years and presurgical investigations at 25 years showed a lateral frontal epileptic focus with spread to Broca's area and the frontal orbital regions. Histopathology revealed a focal cortical dysplasia, not visible on magnetic resonance imaging. The prolonged but reversible early regression and the residual neuropsychological disorders during adulthood were probably the result of an active left frontal epilepsy, which interfered with language and behaviour during development. Our findings raise the question of the role of focal cortical dysplasia as an aetiology in the syndromes of epilepsy with continuous spike waves during sleep and acquired epileptic aphasia.

Educational achievement in Swiss childhood cancer survivors compared with the general population.

BACKGROUND: The objective of this study was to describe educational achievements of childhood cancer survivors in Switzerland compared with the general population. In particular, the authors investigated educational problems during childhood, final educational achievement in adulthood, and its predictors. METHODS: Childhood cancer survivors who were aged <16 years at diagnosis from 1976 to 2003 who had survived for ≥5 years and were currently ages 20 to 40 years received a postal questionnaire during 2007 to 2009. Controls were respondents of the Swiss Health Survey ages 20 to 40 years. Educational achievement included compulsory schooling, vocational training, upper secondary schooling, and university degree. The analysis was weighted to optimize comparability of the populations. The authors analyzed the association between demographic and clinical predictors and educational achievement using multivariable logistic regression. Subgroup analyses focused on survivors aged ≥27 years. RESULTS: One-third of survivors encountered educational problems during schooling (30% repeated 1 year, and 35% received supportive tutoring). In the total sample, more survivors than controls achieved compulsory schooling only (8.7% vs 5.2%) and fewer acquired a university degree (7.3% vs 11%), but more survivors than controls achieved an upper secondary education (36.1 vs 24.1%). In those aged ≥27 years, differences in compulsory schooling and university education largely disappeared. In survivors and controls, sex, nationality, language region, and migration background were strong predictors of achievement. Survivors of central nervous system tumors or those who had a relapse had poorer outcomes (P < .05). CONCLUSIONS: Childhood cancer survivors encountered problems during schooling and completed professional education with some delay. However, with the exception of patients who had central nervous system tumors and those who experienced a relapse, the final educational achievement in survivors of child cancer was comparable to that of the general population.

Robust Nonlinear Mapping of Soil Contamination Using Support Regression

Spatial data analysis mapping and visualization is of great importance in various fields: environment, pollution, natural hazards and risks, epidemiology, spatial econometrics, etc. A basic task of spatial mapping is to make predictions based on some empirical data (measurements). A number of state-of-the-art methods can be used for the task: deterministic interpolations, methods of geostatistics: the family of kriging estimators (Deutsch and Journel, 1997), machine learning algorithms such as artificial neural networks (ANN) of different architectures, hybrid ANN-geostatistics models (Kanevski and Maignan, 2004; Kanevski et al., 1996), etc. All the methods mentioned above can be used for solving the problem of spatial data mapping. Environmental empirical data are always contaminated/corrupted by noise, and often with noise of unknown nature. That's one of the reasons why deterministic models can be inconsistent, since they treat the measurements as values of some unknown function that should be interpolated. Kriging estimators treat the measurements as the realization of some spatial randomn process. To obtain the estimation with kriging one has to model the spatial structure of the data: spatial correlation function or (semi-)variogram. This task can be complicated if there is not sufficient number of measurements and variogram is sensitive to outliers and extremes. ANN is a powerful tool, but it also suffers from the number of reasons. of a special type ? multiplayer perceptrons ? are often used as a detrending tool in hybrid (ANN+geostatistics) models (Kanevski and Maignank, 2004). Therefore, development and adaptation of the method that would be nonlinear and robust to noise in measurements, would deal with the small empirical datasets and which has solid mathematical background is of great importance. The present paper deals with such model, based on Statistical Learning Theory (SLT) - Support Vector Regression. SLT is a general mathematical framework devoted to the problem of estimation of the dependencies from empirical data (Hastie et al, 2004; Vapnik, 1998). SLT models for classification - Support Vector Machines - have shown good results on different machine learning tasks. The results of SVM classification of spatial data are also promising (Kanevski et al, 2002). The properties of SVM for regression - Support Vector Regression (SVR) are less studied. First results of the application of SVR for spatial mapping of physical quantities were obtained by the authorsin for mapping of medium porosity (Kanevski et al, 1999), and for mapping of radioactively contaminated territories (Kanevski and Canu, 2000). The present paper is devoted to further understanding of the properties of SVR model for spatial data analysis and mapping. Detailed description of the SVR theory can be found in (Cristianini and Shawe-Taylor, 2000; Smola, 1996) and basic equations for the nonlinear modeling are given in section 2. Section 3 discusses the application of SVR for spatial data mapping on the real case study - soil pollution by Cs137 radionuclide. Section 4 discusses the properties of the modelapplied to noised data or data with outliers.