Human capital and the quantity–quality trade-off during the demographic transition

This paper provides an empirical test of the child quantity–quality (QQ) trade-off predicted by unified growth theory. Using individual census returns from the 1911 Irish census, we examine whether children who attended school were from smaller families—as predicted by a standard QQ model. To measure causal effects, we use a selection of models robust to endogeneity concerns which we validate for this application using an Empirical Monte Carlo analysis. Our results show that a child remaining in school between the ages of 14 and 16 caused up to a 27 % reduction in fertility. Our results are robust to alternative estimation techniques with different modeling assumptions, sample selection, and alternative definitions of fertility. These findings highlight the importance of the demographic transition as a mechanism which underpinned the expansion in human capital witnessed in Western economies during the twentieth century.

Factores que influyen en la prevalencia de bullyng en estudiantes de los colegios rurales del Cantón Cuenca, Azuay, 2014.

Objetivo: Determinar los factores que influyen en la prevalencia de bullying en estudiantes de los colegios rurales del Cantón Cuenca, Azuay, 2014. Métodos: Estudio descriptivo transversal con participación de 493 estudiantes (283 hombres y 210 mujeres), de 11 a 19 años de edad. La selección de la muestra se realizó por aleatorización simple. Los datos se obtuvieron a través de una encuesta auto-aplicada, los instrumentos utilizados fueron el cuestionario de intimidación escolar CIE-A (Modificado) y el Test del APGAR Familiar. Los datos se procesaron en el programa SPSS 19. Resultados: La prevalencia de bullying en los estudiantes de los colegios rurales del Cantón Cuenca es del 20.0% en mujeres y 17.3% en varones, el acoso fue más evidente en estudiantes de octavos, novenos y decimos de básica superior 21.9%. El tipo de agresión más frecuente es el daño a la propiedad 98.6%. Los factores de riesgo encontrados fueron ambiente escolar desfavorable 71,4%, familiar desfavorable 71.4%, e individual desfavorable 42.2%. Conclusiones: Se encontró una prevalencia importante del bullying en los estudiantes de los colegios rurales del cantón Cuenca y existe asociación significativa del mismo con los factores familiar, escolar e individual desfavorables

Methodology used in studies reporting chronic kidney disease prevalence : a systematic literature review

BACKGROUND: Many publications report the prevalence of chronic kidney disease (CKD) in the general population. Comparisons across studies are hampered as CKD prevalence estimations are influenced by study population characteristics and laboratory methods. METHODS: For this systematic review, two researchers independently searched PubMed, MEDLINE and EMBASE to identify all original research articles that were published between 1 January 2003 and 1 November 2014 reporting the prevalence of CKD in the European adult general population. Data on study methodology and reporting of CKD prevalence results were independently extracted by two researchers. RESULTS: We identified 82 eligible publications and included 48 publications of individual studies for the data extraction. There was considerable variation in population sample selection. The majority of studies did not report the sampling frame used, and the response ranged from 10 to 87%. With regard to the assessment of kidney function, 67% used a Jaffe assay, whereas 13% used the enzymatic assay for creatinine determination. Isotope dilution mass spectrometry calibration was used in 29%. The CKD-EPI (52%) and MDRD (75%) equations were most often used to estimate glomerular filtration rate (GFR). CKD was defined as estimated GFR (eGFR) <60 mL/min/1.73 m(2) in 92% of studies. Urinary markers of CKD were assessed in 60% of the studies. CKD prevalence was reported by sex and age strata in 54 and 50% of the studies, respectively. In publications with a primary objective of reporting CKD prevalence, 39% reported a 95% confidence interval. CONCLUSIONS: The findings from this systematic review showed considerable variation in methods for sampling the general population and assessment of kidney function across studies reporting CKD prevalence. These results are utilized to provide recommendations to help optimize both the design and the reporting of future CKD prevalence studies, which will enhance comparability of study results.

Tackling self-selection into treatment and self-selection into the sample biases in VAA research

Self‐selection into treatment and self‐selection into the sample are major concerns of VAA research and need to be controlled for if the aim is to deduce causal effects from VAA use in observational data. This paper focuses on the methodological aspects of VAA research and outlines omnipresent endogeneity issues, partly imposed through unobserved factors that affect both whether individuals chose to use VAAs and their electoral behavior. We promote using Heckman selection models and apply various versions of the model to data from the Swiss electorate and smartvote users in order to see to what extent selection biases interfere with the estimated effects of interest.

Finite-Sample Simulation-Based Inference in VAR Models with Applications to Order Selection and Causality Testing

Statistical tests in vector autoregressive (VAR) models are typically based on large-sample approximations, involving the use of asymptotic distributions or bootstrap techniques. After documenting that such methods can be very misleading even with fairly large samples, especially when the number of lags or the number of equations is not small, we propose a general simulation-based technique that allows one to control completely the level of tests in parametric VAR models. In particular, we show that maximized Monte Carlo tests [Dufour (2002)] can provide provably exact tests for such models, whether they are stationary or integrated. Applications to order selection and causality testing are considered as special cases. The technique developed is applied to quarterly and monthly VAR models of the U.S. economy, comprising income, money, interest rates and prices, over the period 1965-1996.

Validity of an experimental underwater demolition team selection battery for an officer sample /

Bibliographical footnotes.

Optimal Budget-Constrained Sample Allocation for Selection Decisions with Multiple Uncertain Attributes

A decision-maker, when faced with a limited and fixed budget to collect data in support of a multiple attribute selection decision, must decide how many samples to observe from each alternative and attribute. This allocation decision is of particular importance when the information gained leads to uncertain estimates of the attribute values as with sample data collected from observations such as measurements, experimental evaluations, or simulation runs. For example, when the U.S. Department of Homeland Security must decide upon a radiation detection system to acquire, a number of performance attributes are of interest and must be measured in order to characterize each of the considered systems. We identified and evaluated several approaches to incorporate the uncertainty in the attribute value estimates into a normative model for a multiple attribute selection decision. Assuming an additive multiple attribute value model, we demonstrated the idea of propagating the attribute value uncertainty and describing the decision values for each alternative as probability distributions. These distributions were used to select an alternative. With the goal of maximizing the probability of correct selection we developed and evaluated, under several different sets of assumptions, procedures to allocate the fixed experimental budget across the multiple attributes and alternatives. Through a series of simulation studies, we compared the performance of these allocation procedures to the simple, but common, allocation procedure that distributed the sample budget equally across the alternatives and attributes. We found the allocation procedures that were developed based on the inclusion of decision-maker knowledge, such as knowledge of the decision model, outperformed those that neglected such information. Beginning with general knowledge of the attribute values provided by Bayesian prior distributions, and updating this knowledge with each observed sample, the sequential allocation procedure performed particularly well. These observations demonstrate that managing projects focused on a selection decision so that the decision modeling and the experimental planning are done jointly, rather than in isolation, can improve the overall selection results.

Petroleomics By Electrospray Ionization Ft-icr Mass Spectrometry Coupled To Partial Least Squares With Variable Selection Methods: Prediction Of The Total Acid Number Of Crude Oils.

Negative-ion mode electrospray ionization, ESI(-), with Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) was coupled to a Partial Least Squares (PLS) regression and variable selection methods to estimate the total acid number (TAN) of Brazilian crude oil samples. Generally, ESI(-)-FT-ICR mass spectra present a power of resolution of ca. 500,000 and a mass accuracy less than 1 ppm, producing a data matrix containing over 5700 variables per sample. These variables correspond to heteroatom-containing species detected as deprotonated molecules, [M - H](-) ions, which are identified primarily as naphthenic acids, phenols and carbazole analog species. The TAN values for all samples ranged from 0.06 to 3.61 mg of KOH g(-1). To facilitate the spectral interpretation, three methods of variable selection were studied: variable importance in the projection (VIP), interval partial least squares (iPLS) and elimination of uninformative variables (UVE). The UVE method seems to be more appropriate for selecting important variables, reducing the dimension of the variables to 183 and producing a root mean square error of prediction of 0.32 mg of KOH g(-1). By reducing the size of the data, it was possible to relate the selected variables with their corresponding molecular formulas, thus identifying the main chemical species responsible for the TAN values.

Genome-wide SNP genotyping highlights the role of natural selection in Plasmodium falciparum population divergence

Background: The malaria parasite Plasmodium falciparum exhibits abundant genetic diversity, and this diversity is key to its success as a pathogen. Previous efforts to study genetic diversity in P. falciparum have begun to elucidate the demographic history of the species, as well as patterns of population structure and patterns of linkage disequilibrium within its genome. Such studies will be greatly enhanced by new genomic tools and recent large-scale efforts to map genomic variation. To that end, we have developed a high throughput single nucleotide polymorphism (SNP) genotyping platform for P. falciparum. Results: Using an Affymetrix 3,000 SNP assay array, we found roughly half the assays (1,638) yielded high quality, 100% accurate genotyping calls for both major and minor SNP alleles. Genotype data from 76 global isolates confirm significant genetic differentiation among continental populations and varying levels of SNP diversity and linkage disequilibrium according to geographic location and local epidemiological factors. We further discovered that nonsynonymous and silent (synonymous or noncoding) SNPs differ with respect to within-population diversity, interpopulation differentiation, and the degree to which allele frequencies are correlated between populations. Conclusions: The distinct population profile of nonsynonymous variants indicates that natural selection has a significant influence on genomic diversity in P. falciparum, and that many of these changes may reflect functional variants deserving of follow-up study. Our analysis demonstrates the potential for new high-throughput genotyping technologies to enhance studies of population structure, natural selection, and ultimately enable genome-wide association studies in P. falciparum to find genes underlying key phenotypic traits.

Miniaturized structures for removal or selection of particles from liquid flow

The aim of this work was the development of miniaturized structures useful for retention and/or selection of particles and viscous substances from a liquid flow. The proposed low costs structures are similar to macroscopic wastewater treatment systems, named baffles, and allow disassemble. They were simulated using FEMLAB 3.2b package and manufactured in acrylic with conventional tools. Tests for retention or selection of particles in water or air and viscous fluids in water were carried out. Either in air or water particles with 50 mu m diameter will be retained but not with 13 mu m diameter. In aqueous flow, it is also possible the retention of viscous samples, such as silicone 350 cSt. The simulated results showed good agreement with experimental measurements. These miniaturized structures can be useful in sample pretreatment for chemical analysis and microorganism manipulation. (C) 2007 Elsevier B.V. All rights reserved.

The Fornax Cluster Spectroscopic Survey: a sample of confirmed cluster dwarfs

The Fornax Cluster Spectroscopic Survey (FCSS) project utilizes the Two-degree Field (2dF) multi-object spectrograph on the Anglo-Australian Telescope (AAT). Its aim is to obtain spectra for a complete sample of all 14 000 objects with 16 5 less than or equal to b(j) less than or equal to 19 7 irrespective of their morphology in a 12 deg(2) area centred on the Fornax cluster. A sample of 24 Fornax cluster members has been identified from the first 2dF field (3.1 deg(2) in area) to be completed. This is the first complete sample of cluster objects of known distance with well-defined selection limits. Nineteen of the galaxies (with -15.8 < M-B < 12.7) appear to be conventional dwarf elliptical (dE) or dwarf S0 (dS0) galaxies. The other five objects (with -13.6 < M-B < 11.3) are those galaxies which were described recently by Drinkwater et al. and labelled 'ultracompact dwarfs' (UCDs). A major result is that the conventional dwarfs all have scale sizes alpha greater than or similar to 3 arcsec (similar or equal to300 pc). This apparent minimum scale size implies an equivalent minimum luminosity for a dwarf of a given surface brightness. This produces a limit on their distribution in the magnitude-surface brightness plane, such that we do not observe dEs with high surface brightnesses but faint absolute magnitudes. Above this observed minimum scale size of 3 arcsec, the dEs and dS0s fill the whole area of the magnitude-surface brightness plane sampled by our selection limits. The observed correlation between magnitude and surface brightness noted by several recent studies of brighter galaxies is not seen with our fainter cluster sample. A comparison of our results with the Fornax Cluster Catalog (FCC) of Ferguson illustrates that attempts to determine cluster membership solely on the basis of observed morphology can produce significant errors. The FCC identified 17 of the 24 FCSS sample (i.e. 71 per cent) as being 'cluster' members, in particular missing all five of the UCDs. The FCC also suffers from significant contamination: within the FCSS's field and selection limits, 23 per cent of those objects described as cluster members by the FCC are shown by the FCSS to be background objects.

Evaluation of various pre-treatments for the dehydration of banana and selection of suitable drying models

The thin-layer drying behaviour of bananas in a beat pump dehumidifier dryer was examined. Four pre-treatments (blanching, chilling, freezing and combined blanching and freezing) were applied to the bananas, which were dried at 50 degreesC with an air velocity of 3.1 m s(-1) and with the relative humidity of the inlet air of 10-35%. Three drying models, the simple model, the two-term exponential model and the Page model were examined. All models were evaluated using three statistical measures, correlation coefficient, root means square error, and mean absolute percent error. Moisture diffusivity was calculated based on the diffusion equation for an infinite cylindrical shape using the slope method. The rate of drying was higher for the pre-treatments involving freezing. The sample which was blanched only did not show any improvement in drying rate. In fact, a longer drying time resulted due to water absorption during blanching. There was no change in the rate for the chilled sample compared with the control. While all models closely fitted the drying data, the simple model showed greatest deviation from the experimental results. The two-term exponential model was found to be the best model for describing the drying curves of bananas because its parameters represent better the physical characteristics of the drying process. Moisture diffusivities of bananas were in the range 4.3-13.2 x 10(-10) m(2)s(-1). (C) 2002 Published by Elsevier Science Ltd.

A study of the interaction between national and corporate culture in a selection of Irish based companies

This research studies the phenomenon of national and corporate culture. National culture is the culture the members of a country share and corporate culture is a subculture which members of an organisation share (Schein, 1992). The objective of this research is to reveal if the employees within equivalent Irish and American companies share the same corporate and national culture and to ascertain if, within each company, there is a link between national culture and corporate culture. The object of this study is achieved by replicating research which was conducted by Shing (1997) in Taiwan. Hypotheses and analytical tools developed by Shing are employed in the current study to allow comparison of results between Shing’s study and the current study. The methodology used, called for the measurement and comparison of national and corporate culture in two equivalent companies within the same industry. The two companies involved in this study are both located in Ireland and are of American and Irish origin. A sample of three hundred was selected and the response rate was 54%. The findings from this research are: (1) The two companies involved had different corporate cultures, (2) They had the same national culture, (3) There was no link between national culture and corporate culture within either company, (4) The findings were not similar to those of Shing (1997). The implication of these findings is that national and corporate culture are separate phenomena therefore corporate culture is not a response to national culture. The results of this research are not reflected in the finding’s of Shing (1997), therefore they are context specific. The core recommendation for management is that, corporate culture should take account of national culture. This is because although employees recognise the espoused values of corporate culture (Schein, 1992), they are at the same time influenced by a much stronger force, their national culture.

Effect of training-sample size and classification difficulty on the accuracy of genomic predictors.

Introduction: As part of the MicroArray Quality Control (MAQC)-II project, this analysis examines how the choice of univariate feature-selection methods and classification algorithms may influence the performance of genomic predictors under varying degrees of prediction difficulty represented by three clinically relevant endpoints. Methods: We used gene-expression data from 230 breast cancers (grouped into training and independent validation sets), and we examined 40 predictors (five univariate feature-selection methods combined with eight different classifiers) for each of the three endpoints. Their classification performance was estimated on the training set by using two different resampling methods and compared with the accuracy observed in the independent validation set. Results: A ranking of the three classification problems was obtained, and the performance of 120 models was estimated and assessed on an independent validation set. The bootstrapping estimates were closer to the validation performance than were the cross-validation estimates. The required sample size for each endpoint was estimated, and both gene-level and pathway-level analyses were performed on the obtained models. Conclusions: We showed that genomic predictor accuracy is determined largely by an interplay between sample size and classification difficulty. Variations on univariate feature-selection methods and choice of classification algorithm have only a modest impact on predictor performance, and several statistically equally good predictors can be developed for any given classification problem.

Measuring intergenerational earnings mobility in Spain: a selection-bias-free approach

This paper analyses intergenerational earnings mobility in Spain correcting for different selection biases. We address the co-residence selection problem by combining information from two samples and using the two-sample two-stage least square estimator. We find a small decrease in elasticity when we move to younger cohorts. Furthermore, we find a higher correlation in the case of daughters than in the case of sons; however, when we consider the employment selection in the case of daughters, by adopting a Heckman-type correction method, the diference between sons and daughters disappears. By decomposing the sources of earnings elasticity across generations, we find that the correlation between child's and father's occupation is the most important component. Finally, quantile regressions estimates show that the influence of the father's earnings is greater when we move to the lower tail of the offspring's earnings distribution, especially in the case of daughters' earnings.