Model Diagnostics in the presence of measurement error

The problem of using information available from one variable X to make inferenceabout another Y is classical in many physical and social sciences. In statistics this isoften done via regression analysis where mean response is used to model the data. Onestipulates the model Y = µ(X) +ɛ. Here µ(X) is the mean response at the predictor variable value X = x, and ɛ = Y - µ(X) is the error. In classical regression analysis, both (X; Y ) are observable and one then proceeds to make inference about the mean response function µ(X). In practice there are numerous examples where X is not available, but a variable Z is observed which provides an estimate of X. As an example, consider the herbicidestudy of Rudemo, et al. [3] in which a nominal measured amount Z of herbicide was applied to a plant but the actual amount absorbed by the plant X is unobservable. As another example, from Wang [5], an epidemiologist studies the severity of a lung disease, Y , among the residents in a city in relation to the amount of certain air pollutants. The amount of the air pollutants Z can be measured at certain observation stations in the city, but the actual exposure of the residents to the pollutants, X, is unobservable and may vary randomly from the Z-values. In both cases X = Z+error: This is the so called Berkson measurement error model.In more classical measurement error model one observes an unbiased estimator W of X and stipulates the relation W = X + error: An example of this model occurs when assessing effect of nutrition X on a disease. Measuring nutrition intake precisely within 24 hours is almost impossible. There are many similar examples in agricultural or medical studies, see e.g., Carroll, Ruppert and Stefanski [1] and Fuller [2], , among others. In this talk we shall address the question of fitting a parametric model to the re-gression function µ(X) in the Berkson measurement error model: Y = µ(X) + ɛ; X = Z + η; where η and ɛ are random errors with E(ɛ) = 0, X and η are d-dimensional, and Z is the observable d-dimensional r.v.

Impact of the Sanitary and Phyto Sanitary Agreement on the Exports of Marine Products from India with Special Reference to Kerala

Fish and fishery products are regarded as healthy foods and there has been a significant increase in their global trade. Besides that, trade liberalization policies, globalization of food systems and technological innovations have furthered the increase in international trade in fish and fishery products.Fish and fishery product exports have a significant place in the export basket of India. Export earnings of India from fishery products increased from ` 4 crores in 1960-61to ` 12901.47 crores in 2010-11(MPEDA, 2012). The share of export earnings from fish and fishery products as a percentage of total agricultural exports of India increased from a low of 1.76 percent in 1960-61 to a high of 25.06 percent in 1994-95. But its share declined to 16.60 percent in the following year. Though its share in agricultural exports of the country has declined since then, in 2010-11, marine product exports accounted for 9.61 percent of total agricultural exports of India representing a significant share.

Error estimates for approximate approximations on compact intervals

The aim of this paper is the investigation of the error which results from the method of approximate approximations applied to functions defined on compact in- tervals, only. This method, which is based on an approximate partition of unity, was introduced by V. Mazya in 1991 and has mainly been used for functions defied on the whole space up to now. For the treatment of differential equations and boundary integral equations, however, an efficient approximation procedure on compact intervals is needed. In the present paper we apply the method of approximate approximations to functions which are defined on compact intervals. In contrast to the whole space case here a truncation error has to be controlled in addition. For the resulting total error pointwise estimates and L1-estimates are given, where all the constants are determined explicitly.

Approximate solutions and error estimates for a Stokes boundary value problem

The aim of this paper is the numerical treatment of a boundary value problem for the system of Stokes' equations. For this we extend the method of approximate approximations to boundary value problems. This method was introduced by V. Maz'ya in 1991 and has been used until now for the approximation of smooth functions defined on the whole space and for the approximation of volume potentials. In the present paper we develop an approximation procedure for the solution of the interior Dirichlet problem for the system of Stokes' equations in two dimensions. The procedure is based on potential theoretical considerations in connection with a boundary integral equations method and consists of three approximation steps as follows. In a first step the unknown source density in the potential representation of the solution is replaced by approximate approximations. In a second step the decay behavior of the generating functions is used to gain a suitable approximation for the potential kernel, and in a third step Nyström's method leads to a linear algebraic system for the approximate source density. For every step a convergence analysis is established and corresponding error estimates are given.

An Analysis of the Effect of Gaussian Error in Object Recognition

Object recognition is complicated by clutter, occlusion, and sensor error. Since pose hypotheses are based on image feature locations, these effects can lead to false negatives and positives. In a typical recognition algorithm, pose hypotheses are tested against the image, and a score is assigned to each hypothesis. We use a statistical model to determine the score distribution associated with correct and incorrect pose hypotheses, and use binary hypothesis testing techniques to distinguish between them. Using this approach we can compare algorithms and noise models, and automatically choose values for internal system thresholds to minimize the probability of making a mistake.

Moderating effects of management control systems and innovation on performance. Simple methods for correcting the effects of measurement error for interaction effects in small samples

In the accounting literature, interaction or moderating effects are usually assessed by means of OLS regression and summated rating scales are constructed to reduce measurement error bias. Structural equation models and two-stage least squares regression could be used to completely eliminate this bias, but large samples are needed. Partial Least Squares are appropriate for small samples but do not correct measurement error bias. In this article, disattenuated regression is discussed as a small sample alternative and is illustrated on data of Bisbe and Otley (in press) that examine the interaction effect of innovation and style of use of budgets on performance. Sizeable differences emerge between OLS and disattenuated regression

The agreement between ipsative and normative questionnaires using compositional data analysis techniques

The main instrument used in psychological measurement is the self-report questionnaire. One of its major drawbacks however is its susceptibility to response biases. A known strategy to control these biases has been the use of so-called ipsative items. Ipsative items are items that require the respondent to make between-scale comparisons within each item. The selected option determines to which scale the weight of the answer is attributed. Consequently in questionnaires only consisting of ipsative items every respondent is allotted an equal amount, i.e. the total score, that each can distribute differently over the scales. Therefore this type of response format yields data that can be considered compositional from its inception. Methodological oriented psychologists have heavily criticized this type of item format, since the resulting data is also marked by the associated unfavourable statistical properties. Nevertheless, clinicians have kept using these questionnaires to their satisfaction. This investigation therefore aims to evaluate both positions and addresses the similarities and differences between the two data collection methods. The ultimate objective is to formulate a guideline when to use which type of item format. The comparison is based on data obtained with both an ipsative and normative version of three psychological questionnaires, which were administered to 502 first-year students in psychology according to a balanced within-subjects design. Previous research only compared the direct ipsative scale scores with the derived ipsative scale scores. The use of compositional data analysis techniques also enables one to compare derived normative score ratios with direct normative score ratios. The addition of the second comparison not only offers the advantage of a better-balanced research strategy. In principle it also allows for parametric testing in the evaluation

Evaluación de la psicopatología del preescolar mediante el Early Childhood Inventory-4 (ECI-4): concordancia entre padres y maestros.= Assessment of psychopathology in preschool age children through the Early Childhood Inventory-4 (ECI-4): Agreement among parents and teachers

El objetivo principal de este estudio es conocer la concordancia entre informantes, padres y maestros, en cada una de las dimensiones o categorías diagnósticas del Early Childhood Inventory-4 (ECI-4). Además, se pretende analizar la influencia de la presencia de problemas de salud en los padres en la descripción y valoración de la conducta de una muestra de 204 alumnos de preescolar (3 a 6 años) de perfiles socioeconómicos diferentes. Los resultados indican que los padres tienden a valorar con mayor severidad los síntomas, observándose una mayor concordancia entre informantes en los relativos a los trastornos del desarrollo

Correcting Measurement Error Bias in Interaction Models with Small Samples

Several methods have been suggested to estimate non-linear models with interaction terms in the presence of measurement error. Structural equation models eliminate measurement error bias, but require large samples. Ordinary least squares regression on summated scales, regression on factor scores and partial least squares are appropriate for small samples but do not correct measurement error bias. Two stage least squares regression does correct measurement error bias but the results strongly depend on the instrumental variable choice. This article discusses the old disattenuated regression method as an alternative for correcting measurement error in small samples. The method is extended to the case of interaction terms and is illustrated on a model that examines the interaction effect of innovation and style of use of budgets on business performance. Alternative reliability estimates that can be used to disattenuate the estimates are discussed. A comparison is made with the alternative methods. Methods that do not correct for measurement error bias perform very similarly and considerably worse than disattenuated regression

Do parents and children know each other? : a study about agreement on personality within families. '??Se conocen bien los padres y los hijos? : un estudio sobre el grado de acuerdo en personalidad dentro de las familias'

Resumen tomado de la publicaci??n. Resumen tambi??n en ingl??s

Bondad de ajuste en ??tems polit??micos : tasas de error tipo I y potencia de tres ??ndices de ajuste

Resumen tomado de la publicaci??n

A vueltas con el error de Otelo : aplicación del modelo de control de fuentes a la credibilidad del testimonio y su afectación por la carga emocional.

Resumen tomado de la publicación

Retinoscopía estática: variabilidad interobservadores entre docentes y estudiantes de optometría en una institución universitaria de Bogotá D.C.

Introducción: el gold estándar para el error refractivo es la retinoscopía. Los docentes de optometría al evaluar estudiantes, aceptan una diferencia de ±0,50D en la refracción pero no se ha evaluado estadísticamente si es adecuado para ametropías bajas y altas. El objetivo fue cuantificar el grado de concordancia interobservadores en retinoscopía estática entre docentes y estudiantes, para ametropías altas y bajas. Metodología: estudio de concordancia entre 4 observadores en 40 ojos, 20 con ametropías altas y 20 con bajas; muestreo no probabilístico por conveniencia. Análisis estadístico con coeficiente de correlación intraclase, confiabilidad 95%, poder 90%, y con método gráfico de límites de acuerdo al 95%. Resultados: concordancia para el equivalente esférico entre docentes 0,96 y entre estudiantes 0,56. En estudiantes concordancia de 0,89 para defectos refractivos bajos y docentes 0,96 para defectos altos. Concordancia entre cuatro examinadores 0,78, defectos bajos 0,86 y para altos 0,67. Margen de error entre docentes ±0,87D y estudiantes ±3,15D. En defectos bajos ±0,61D para docentes y ±0,80D para estudiantes y en defectos altos ±1,10D y ±4,22D respectivamente. Discusión: hubo mayor confiabilidad en retinoscopía entre profesionales experimentados. Se comparó la concordancia entre docentes y estudiantes, por eso puede haberse encontrado menor concordancia que la descrita por otros estudios que compararon entre profesionales a pesar haber sido elegidos por sus buenas calificaciones. Se deben formular estrategias de enseñanza que permitan reducir los márgenes de error obtenidos y mejorar la concordancia entre docentes y estudiantes.

Agreement in interpersonal perception as a predictor of group performance

Resumen tomado de la publicaci??n

El currículum integrat : una errada de les autoritats educatives. 'El currículum integrado : un error de las autoridades educativas'.

Resumen tomado de la revista