Influence properties of partial squares regression.

In this paper, we compute the influence function for partial least squares regression. Thereunto, we design two alternative algorithms, according to the PLS algorithm used. One algorithm for the computation of the influence function is based on the Helland PLS algorithm, whilst the other is compatible with SIMPLS.The calculation of the influence function leads to new influence diagnostic plots for PLS. An alternative to the well known Cook distance plot is proposed, as well as a variant which is sample specific.Moreover, a novel estimate of prediction variance is deduced. The validity of the latter is corroborated by dint of a Monte Carlo simulation.Influence function; Design; Algorithms; Simulation;

Influence properties of partial least squares regression.

Regression; Partial least squares; Least-squares; Squares; Squares regression;

Robust continuum regression.

Several applications of continuum regression (CR) to non-contaminated data have shown that a significant improvement in predictive power can be obtained compared to the three standard techniques which it encompasses (ordinary least squares (OLS), principal component regression (PCR) and partial least squares (PLS)). For contaminated data continuum regression may yield aberrant estimates due to its non-robustness with respect to outliers. Also for data originating from a distribution which significantly differs from the normal distribution, continuum regression may yield very inefficient estimates. In the current paper, robust continuum regression (RCR) is proposed. To construct the estimator, an algorithm based on projection pursuit (PP) is proposed. The robustness and good efficiency properties of RCR are shown by means of a simulation study. An application to an X-ray fluorescence analysis of hydrometallurgical samples illustrates the method's applicability in practice.Regression; Applications; Data; Ordinary least squares; Least-squares; Squares; Partial least squares; Yield; Outliers; Distribution; Estimator; Projection-pursuit; Robustness; Efficiency; Simulation; Studies;

Robust continuum regression.

Several applications of continuum regression to non-contaminated data have shown that a significant improvement in predictive power can be obtained compared to the three standard techniques which it encompasses (Ordinary least Squares, Principal Component Regression and Partial Least Squares). For contaminated data continuum regression may yield aberrant estimates due to its non-robustness with respect to outliers. Also for data originating from a distribution which significantly differs from the normal distribution, continuum regression may yield very inefficient estimates. In the current paper, robust continuum regression (RCR) is proposed. To construct the estimator, an algorithm based on projection pursuit is proposed. The robustness and good efficiency properties of RCR are shown by means of a simulation study. An application to an X-ray fluorescence analysis of hydrometallurgical samples illustrates the method's applicability in practice.Advantages; Applications; Calibration; Continuum regression (CR); Data; Distribution; Efficiency; Estimator; Least-squares; M-estimators; Methods; Model; Optimal; Ordinary least squares; Outliers; Partial least squares; Precision; Prediction; Projection-pursuit; Regression; Research; Robust continuum regression (RCR); Robust multivariate calibration; Robust regression; Robustness; Simulation; Squares; Studies; Variables; Yield;

Partial robust M-regression.

Partial Least Squares (PLS) is a standard statistical method in chemometrics. It can be considered as an incomplete, or 'partial', version of the Least Squares estimator of regression, applicable when high or perfect multicollinearity is present in the predictor variables. The Least Squares estimator is well-known to be an optimal estimator for regression, but only when the error terms are normally distributed. In the absence of normality, and in particular when outliers are in the data set, other more robust regression estimators have better properties. In this paper a 'partial' version of M-regression estimators will be defined. If an appropriate weighting scheme is chosen, partial M-estimators become entirely robust to any type of outlying points, and are called Partial Robust M-estimators. It is shown that partial robust M-regression outperforms existing methods for robust PLS regression in terms of statistical precision and computational speed, while keeping good robustness properties. The method is applied to a data set consisting of EPXMA spectra of archaeological glass vessels. This data set contains several outliers, and the advantages of partial robust M-regression are illustrated. Applying partial robust M-regression yields much smaller prediction errors for noisy calibration samples than PLS. On the other hand, if the data follow perfectly well a normal model, the loss in efficiency to be paid for is very small.Advantages; Applications; Calibration; Data; Distribution; Efficiency; Estimator; Least-squares; M-estimators; Methods; Model; Optimal; Ordinary least squares; Outliers; Partial least squares; Precision; Prediction; Projection-pursuit; Regression; Robust regression; Robustness; Simulation; Spectometric quantization; Squares; Studies; Variables; Yield;

Microeconomic institutions and personnel economics for health care delivery: a formal exploration of what matters to health workers in Rwanda

Background: Most developing countries face important challenges regarding the quality of health care and there is a growing consensus that health workers play a key role in this process. Our understanding as to what are the key institutional challenges in human resources, and their underlying driving forces, is more limited. A conceptual framework that structures existing insights and provides concrete directions for policy making is also missing. Methods: To gain a bottom up perspective we gather qualitative data through semi-structured interviews with different levels of health workers and users of health services in rural and urban Rwanda. We conducted discussions with 48 health workers and 25 users of health services in nine different groups in 2005. We maximized within-group heterogeneity by selecting participants using specific criteria that affect health worker performance and career choice. The discussion were analysed electronically, to identify key themes and insights, and are documented with a descriptive quantitative analysis relating to the associations between quotations. The findings from this research are then revisited ten years later making use of detailed follow up studies that have been carried out since then. Findings: The original discussions identified both key challenges in human resources for health, and driving forces of these challenges, as well as possible solutions. Two sets of issues were highlighted: those related to the size and distribution of the workforce, and those related to health workers’ on-the-job performance. Among the latter, four categories were identified: health workers’ poor attitudes towards patients, absenteeism, corruption and embezzlement, and lack of medical skills among some categories of health workers. The discussion suggest that four components constitute the deeper causal factors, which are, ranked in order of ease of malleability: incentives, monitoring arrangements, professional and workplace norms and intrinsic motivation. Three institutional innovations are identified that aim at improving performance: performance pay, community health workers and increased attention to training of health workers. Revisiting the findings from this primary research making use of later in depth studies, the analysis demonstrates their continued relevance and usefulness. We discuss how the different factors affect the quality of care by impacting on health worker performance and labour market choices, making use of insights from economics and development studies on the role of institutions. Conclusion: The study results indicates that health care quality to an important degree depends on four institutional factors at the micro level that strongly impact on health workers performance and career choice, and which deserve more attention in applied research and policy reform. The analysis also helps to identify ways forwards, which fit well with the Ministry’s most recent strategic plan

Preferences and skills of Indian public sector teachers

With a sample of 700 future public sector primary teachers in India, a Discrete Choice Experiment is used to measure job preferences, particularly regarding location. General skills are also tested. Urban origin teachers and women are more averse to remote locations than rural origin teachers and men respectively. Women would require a 26-73 percent increase in salary for moving to a remote location. The results suggest that existing caste and gender quotas can be detrimental for hiring skilled teachers willing to work in remote locations. The most preferred location is home, which supports decentralised hiring, although this could compromise skills

PARL deficiency in mouse causes Complex III defects, coenzyme Q depletion, and Leigh-like syndrome

The mitochondrial intramembrane rhomboid protease PARL has been implicated in diverse functions in vitro, but its physiological role in vivo remains unclear. Here we show that ablation in mouse causes a necrotizing encephalomyelopathy similar to Leigh syndrome, a mitochondrial disease characterized by disrupted energy production. Mice with conditional PARL deficiency in the nervous system, but not in muscle, develop a similar phenotype as germline KOs, demonstrating the vital role of PARL in neurological homeostasis. Genetic modification of two major PARL substrates, PINK1 and PGAM5, do not modify this severe neurological phenotype. brain mitochondria are affected by progressive ultrastructural changes and by defects in Complex III (CIII) activity, coenzyme Q (CoQ) biosynthesis, and mitochondrial calcium metabolism. PARL is necessary for the stable expression of TTC19, which is required for CIII activity, and of COQ4, which is essential in CoQ biosynthesis. Thus, PARL plays a previously overlooked constitutive role in the maintenance of the respiratory chain in the nervous system, and its deficiency causes progressive mitochondrial dysfunction and structural abnormalities leading to neuronal necrosis and Leigh-like syndrome