A measure of interrater absolute agreement for ordinal categorical data

Statistical Methods & Applications - A measure of interrater absolute agreement for ordinal scales is proposed capitalizing on the dispersion index for ordinal variables proposed by Giuseppe...     

Gambling Disorder and Affect Regulation: The Role of Alexithymia and Attachment Style

The aim of the present study was to explore the dimensions of alexithymia and attachment styles in a group of disordered gamblers and to evaluate the relationship between alexithymia, attachment styles, and the severity of gambling disorder. Sixty disordered gamblers diagnosed according to the diagnostic and statistical manual-5 filled out the Kurzfragebogen zum Glücksspielverhalten, the 20-Item Toronto Alexithymia Scale, and the Experiences in Close Relationships-Revised. Approximately 70 % of the sample displayed ‘intermediate’ and ‘severe’ gambling severity levels on the Kurzfragebogen zum Glücksspielverhalten, and 77 % showed ‘high’ or ‘borderline’ levels of alexithymia on the Toronto Alexithymia Scale (mean = 56.40). Regarding attachment styles, 70 % of the sample displayed an ‘insecure’ attachment, with a particularly high prevalence of the ‘fearful’ style (26.66 %). A linear regression analysis revealed that only the anxiety dimension of the Experiences in Close Relationships questionnaire predicted the severity of gambling. Our data appear to confirm that gambling disorder is characterised by emotional and relational dysregulation, and that pathological gambling behaviours may serve as external regulators of internal undifferentiated emotional states.     

Revising a Prognostic Index Developed for Classification Purposes: an Application to Gastric Cancer Data

A prognostic index (PI) is usually derived from a regression model as a weighted mean of the covariates, with weights (partial scores) proportional to the parameter estimates. When a PI is applied to patients other than those considered for its development, the issue of assessing its validity on the new case series is crucial. For this purpose, Van Houwelingen (2000) proposed a method of validation by calibration, which limits overfitting by embedding the original model into a new one, so that only a few parameters will have to be estimated. Here we address the problem of PI validation and revision with the above approach when the PI has classification purposes and it represents the linear predictor of a Weibull model, derived from an accelerated failure time parameterization instead of a proportional hazards one, as originally described by Van Houwelingen. We show that the Van Houwelingen method can be applied in a straightforward manner, provided that the parameterization originally used in the PI model is appropriately taken into account. We also show that model validation and revision can be carried out by modifying the cut-off values used for prognostic grouping without affecting the partial scores of the original PI. This procedure can be applied to simplify the clinician's use of an established PI for classification purposes.     

Inverse Sampling with Unequal Selection Probabilities

In some real situations the population of interest is divided into two groups, of which one contains only a few units. In other cases, the population may be considered as subdivided into two group', for example, if only a few units display a value of the variable of interest which is highly different from zero, while all the other units show a value equal to or near zero. In both cases, inverse sampling is more efficient than classical fixed sample-size designs to obtain the parameter estimators for the whole population as well as for its groups (e.g., Salehi and Seber, 2004 Salehi , M. M. , Seber , G. A. F. ( 2004 ). A general inverse sampling scheme and its application to adaptive cluster sampling . Austral. NZ J. Statist. 46 : 483 – 494 .[Crossref], [Web of Science ®] , [Google Scholar]). In fact, in this design the procedure selection continues until a prefixed number of units with the characteristic of interest is sampled. Since it is not known a priori to which group the population units belong, the sample size is a random variable. Christman and Lan (2001 Christman , M. C. , Lan , F. ( 2001 ). Inverse adaptive cluster sampling . Biometrics 57 : 1096 – 1105 .[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]) and Salehi and Seber (2001 Salehi , M. M. , Seber , G. A. F. ( 2001 ). A new proof of Murthy's estimator which applies to sequential sampling . Austral. NZ J. Statist. 43 : 281 – 286 . [Google Scholar] 2004 Salehi , M. M. , Seber , G. A. F. ( 2004 ). A general inverse sampling scheme and its application to adaptive cluster sampling . Austral. NZ J. Statist. 46 : 483 – 494 .[Crossref], [Web of Science ®] , [Google Scholar]) considered inverse sampling designs when all the population units have equal selection probabilities. In this article, we consider the general case in which the units may have unequal probabilities of being included in the sample. In fact, in many real situations different units may have different selection probabilities because of some inherent features of the sampling procedure, or in order to obtain better estimates. We derive unbiased estimators of the totals of the two groups, their variance and the corresponding unbiased variance estimators in inverse sampling with replacement. Finally, we derive similar results for more complex designs, where the selection procedure stops before observing the prefixed number of units from the rare group.     

A Permutation Approach to Split-Plot Experiments

Split-plot design may be refer to a common experimental setting where a particular type of restricted randomization has occurred during a planned experiment. The aim of this article is to suggest a new method to perform inference on split-plot experiments by combination-based permutation tests. This novel nonparametric approach has been studied and validated using a Monte Carlo simulation study where we compared it with the parametric and nonparametric procedures proposed in the literature. Results suggest that in each experimental situation where normality is hard to justify and especially when errors have heavy-tailed distribution, the proposed nonparametric procedure can be considered as a valid solution.     

Effects of long-acting testosterone undecanoate on bone mineral density in middle-aged men with late-onset hypogonadism and metabolic syndrome: results from a 36 months controlled study

We evaluated the effects of long-term testosterone replacement therapy (TRT) on the bone mineral density (BMD) in obese patients with metabolic syndrome (MS) and late-onset hypogonadism (LOH). Sixty men (mean age 57 ± 10) with low serum testosterone (T < 320 ng/dL) and MS regardless the presence of osteoporosis were enrolled. Forty men received intramuscular T-undecanoate (TU) four times/year for 36 months and 20 age-matched hypogonadal men with MS in whom T treatment was contraindicated were used as controls. Hormonal, biochemical markers, vertebral and femoral BMD by dual-energy x-ray absorptiometry were measured. At baseline, overall patients had mild osteopenia (lumbar BMD= 0.891 ± 0.097 g/cm(2); femoral BMD= 0.847 ± 0.117 g/cm(2)). TU induced a significant improvement of bone mass after 36 months (lumbar BMD=1.053 ± 0.145 g/cm(2); p < 0.002; femoral BMD=0.989 ± 0.109; p < 0.003 g/cm(2)) with a 5%/year increase and a significant reduction in hs-CRP without changes in body mass index. A direct relationship between serum T and BMD increments at the lumbar (r(2)?= 0.66, p < 0.0001) and femoral (r(2)?=0.52, p < 0.0001) sites was demonstrated. Study adherence was 50% without serious side effects. Long-term TRT in middle-aged men with LOH and MS determines a significant increase in both vertebral and femoral BMD related to increased serum T levels, probably independently from estradiol modifications.     

Fractional Moments and Maximum Entropy: Geometric Meaning

We consider the problem of recovering a probability density on a bounded or unbounded subset D of [0, ∞), from the knowledge of its sequence of fractional moments within a maximum entropy (MaxEnt) setup. Based upon entropy convergence results previously formulated, the fractional moments are selected so that the entropy of the MaxEnt approximation be minimum. A geometric interpretation of the reconstruction procedure is formulated as follows: the two moment curves generated by the unknown density and its MaxEnt approximation are interpolating in Hermite-Birkoff sense; that is, they are both interpolating and tangent at the selected nodes.