Testofen,a specialised Trigonella foenum-graecum seed extract reduces age-related symptoms of androgen decrease,increases testosterone levels and improves sexual function in healthy aging males in a double-blind randomised clinical study

This study examined the effect of Testofen, a specialised Trigonella foenum-graecum seed extract on the symptoms of possible androgen deficiency, sexual function and serum androgen concentrations in healthy aging males. This was a double-blind, randomised, placebo-controlled trial involving 120 healthy men aged between 43 and 70 years of age. The active treatment was standardised Trigonella foenum-graecum seed extract at a dose of 600?mg/day for 12 weeks. The primary outcome measure was the change in the Aging Male Symptom questionnaire (AMS), a measure of possible androgen deficiency symptoms; secondary outcome measures were sexual function and serum testosterone. There was a significant decrease in AMS score over time and between the active and placebo groups. Sexual function improved, including number of morning erections and frequency of sexual activity. Both total serum testosterone and free testosterone increased compared to placebo after 12 weeks of active treatment. Trigonella foenum-graecum seed extract is a safe and effective treatment for reducing symptoms of possible androgen deficiency, improves sexual function and increases serum testosterone in healthy middle-aged and older men.     

Small Area Estimation Using Estimated Population Level Auxiliary Data

Unit level linear mixed models are often used in small area estimation (SAE), and the empirical best linear unbiased prediction (EBLUP) is widely used for the estimation of small area means under such models. However, EBLUP requires population level auxiliary data, atleast area specific aggregated values. Sometimes population level auxiliary data is either not available or not consistent with the survey data. We describe a SAE method that uses estimated population auxiliary information. Empirical results show that proposed method for SAE produces an efficient set of small area estimates.     

Autocovariance Estimation in Regression with a Discontinuous Signal and m‐Dependent Errors: A Difference‐Based Approach

We discuss a class of difference‐based estimators for the autocovariance in nonparametric regression when the signal is discontinuous and the errors form a stationary m‐dependent process. These estimators circumvent the particularly challenging task of pre‐estimating such an unknown regression function. We provide finite‐sample expressions of their mean squared errors for piecewise constant signals and Gaussian errors. Based on this, we derive biased‐optimized estimates that do not depend on the unknown autocovariance structure. Notably, for positively correlated errors, that part of the variance of our estimators that depend on the signal is minimal as well. Further, we provide sufficient conditions for ‐consistency; this result is extended to piecewise Hölder regression with non‐Gaussian errors. We combine our biased‐optimized autocovariance estimates with a projection‐based approach and derive covariance matrix estimates, a method that is of independent interest. An R package, several simulations and an application to biophysical measurements complement this paper.     

Bias in the ordinary least squares estimator in the dynamic linear regression model with autocorrelated disturbances

We consider the bias in the Ordinary Least Squares estimator in the linear regression model with a lagged dependent variable as regressor. Results are obtained with independent and auto-correlated disturbances. Asymptotic results are obtained analytically, and finite sample results based on a Monte Carlo study. The substantial biases found suggest the need for an alternative estimator to Ordinary Least Squares and powerful tests for autocorrelated disturbances in the dynamic model.     

Small Area Estimation for Zero-Inflated Data

The commonly used method of small area estimation (SAE) under a linear mixed model may not be efficient if data contain substantial proportion of zeros than would be expected under standard model assumptions (hereafter zero-inflated data). The authors discuss the SAE for zero-inflated data under a two-part random effects model that account for excess zeros in the data. Empirical results show that proposed method for SAE works well and produces an efficient set of small area estimates. An application to real survey data from the National Sample Survey Office of India demonstrates the satisfactory performance of the method. The authors describe a parametric bootstrap method to estimate the mean squared error (MSE) of the proposed estimator of small areas. The bootstrap estimates of the MSE are compared to the true MSE in simulation study.     

Disaggregate-level estimates of indebtedness in the state of Uttar Pradesh in India: an application of small-area estimation technique

The National Sample Survey Organisation (NSSO) surveys are the main source of official statistics in India, and generate a range of invaluable data at the macro level (e.g. state and national levels). However, the NSSO data cannot be used directly to produce reliable estimates at the micro level (e.g. district or further disaggregate level) due to small sample sizes. There is a rapidly growing demand of such micro-level statistics in India, as the country is moving from centralized to more decentralized planning system. In this article, we employ small-area estimation (SAE) techniques to derive model-based estimates of the proportion of indebted households at district or at other small-area levels in the state of Uttar Pradesh in India by linking data from the Debt–Investment Survey 2002–2003 of NSSO and the Population Census 2001 and the Agriculture Census 2003. Our results show that the model-based estimates are precise and representative. For many small areas, it is even not possible to produce estimates using sample data alone. The model-based estimates generated using SAE are still reliable for such areas. The estimates are expected to provide invaluable information to policy analysts and decision-makers.     

An Optimal Procedure for Sample Coordination Using Multiple Objective Functions and Nearest Proportional to IPPS Size Sampling Designs

The sample coordination problem involves maximization or minimization of overlap of sampling units in different/repeated surveys. Several optimal techniques using transportation theory, controlled rounding, and controlled selection have been suggested in literature to solve the sample coordination problem. In this article, using the multiple objective programming, we propose a method for sample coordination which facilitates variance estimation using the Horvitz–Thompson estimator. The proposed procedure can be applied to any two-sample surveys having identical universe and stratification. Some examples are discussed to demonstrate the utility of the proposed procedure.     

Generalized Symmetric Divergence Measures and the Probability of Error

There are three classical divergence measures exist in the literature on information theory and statistics. These are namely, Jeffryes-Kullback-Leiber (Jeffreys, 1946 Jeffreys , H. ( 1946 ). An invariant form for the prior probability in estimation problems . Proc. Roy. Soc. Lon. Ser. A 186 : 453 – 461 .[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]; Kullback and Leibler, 1951 Kullback , S. , Leibler , R. A. ( 1951 ). On information and sufficiency . Ann. Math. Statist. 22 : 79 – 86 .[Crossref] , [Google Scholar]) J-divergence. Sibson-Burbea-Rao (Sibson, 1969 Sibson , R. ( 1969 ). Information radius . Z. Wahrs. und verw Geb. 14 : 149 – 160 .[Crossref], [Web of Science ®] , [Google Scholar]), Jensen-Shannon divegernce, (Burbea and Rao, 1982 Burbea , J. , Rao , C. R. ( 1982 ). On the convexity of some divergence measures based on entropy functions . IEEE Trans. Inform. Theor. IT-28 : 489 – 495 .[Crossref], [Web of Science ®] , [Google Scholar]), and Taneja (1995 Taneja , I.J. ( 1995 ). New developments in generalized information measures , In: Hawkes , P. W. , Ed., Advances in Imaging and Electron Physics . 91:37–136 . [Google Scholar]). Arithmetic-Geometric divergence. These three measures bear an interesting relationship among each other. The divergence measures like Hellinger (1909 Hellinger , H. ( 1909 ). Neue Begründung der theorie der quadratischen formen von unendlichen vielen Veränderlichen . J. Reine Aug. Math. 136 : 210 – 271 .[Crossref] , [Google Scholar]) discrimination, symmetric χ²-divergence, and triangular discrimination are also known in the literature. In this article, we have considered generalized symmetric divergence measures having the measures given above as particular cases. Bounds on the probability of error are obtained in terms of generalized symmetric divergence measures. Study of bounds on probability of error is extended for the difference of divergence measures.     

Calibration approach for estimating population total with subsampling of non respondents under single- and two-phase sampling

ABSTRACT

Using the calibration approach, the Hansen and Hurwitz (1946 Hansen, M.H., Hurwitz, W.N. (1946). The problem of non response in sample surveys. J. Am. Stat. Assoc. 46:147–190.[Taylor & Francis Online] , [Google Scholar]) technique-based estimator is developed for the situation where the information on auxiliary variable is assumed known for the entire population units. The double-sampling case has also been dealt with. Expressions for the estimator of population total, its variance, and variance estimator are developed. The theoretical results are illustrated with the help of simulation studies. Simulation results show that the proposed calibration approach-based estimator outperforms the Hansen and Hurwitz estimator.     

Promoting Stability and Development in Fragile and Failed States

There is a growing recognition of the threat to international security posed by failed and fragile states, often marred by serious internal conflict that also has the potential of destabilising neighbouring states and providing ungoverned territory that can provide safe haven for terrorists. The inability of their governments to provide basic services is considered a significant contributory factor. Considerable donor efforts have been mobilised in recent years to help with the post‐conflict reconstruction of states emerging from failure, and to halt the slide of fragile states towards failure, but with mixed effect. The international community needs to focus much more squarely on strengthening the emerging state and increasing its domestic legitimacy, rather than on promoting democracy.