Standard empirical models of operating efficiency (OE) and managerial ability (MA) assume a symmetric linear relation of OE and MA with firm performance. However, OE and MA metrics are likely to respond faster to a demand decrease than a demand increase due to cost stickiness and respond faster to negative returns than to positive returns due to accounting conservatism. As predicted, I find large asymmetries in the behavior of OE and MA measures. OE and MA in levels (changes) are 2.4 (1.4) times and 1.5 (1.6) times more sensitive to demand decreases than demand increases. Similarly, OE and MA levels (changes) are 1.7 (1.5) times and 3.6 (2.3) times more sensitive to negative returns than to positive returns. The incremental explanatory power of modeling asymmetry in OE and MA levels (changes) is 20.9% (39.5%) and 263.3% (27.6%), measured as incremental adjusted R2. Cross-sectionally, asymmetry in OE and MA varies with the determinants of cost stickiness: (1) asset intensity and (2) employee intensity. Moreover, the degree of asymmetry also varies with the determinants of accounting conservatism: (1) book-to-market value of equity, (2) leverage, and (3) market capitalization. In addition, demand decline (i.e., cost stickiness) and bad news (i.e., accounting conservatism) during prior and successive periods have an incremental impact on the asymmetry in OE and MA. The standard models of OE and MA do not control for these correlated-omitted variables or incorporate the cost stickiness and accounting conservatism asymmetries, which yield biased measurements and render incorrect regression estimates and inferences. / Business Administration/Accounting

The purpose of this thesis is to investigate how the differences between the study and policy sites impact the performance of benefit function transfer. For this purpose, simulated data are created where all information necessary to conduct the benefit function transfer is available. We consider the six cases of difference between the study and policy sites- scale parameter, substitution possibilities, observable characteristics, population preferences, measurement error in variables, and a case of preference heterogeneity at the study site and fixed preferences at the policy site. These cases of difference were considered one at time and their impact on quality of transfer is investigated. RUM model based on reveled preference was used for this analysis. Function estimated at the study site is transferred to the policy site and willingness to pay for five different cases of policy changes are calculated at the study site. The willingness to pay so calculated is compared with true willingness to pay to evaluate the performance of benefit function transfer. When the study and policy site are different only in terms of scale parameter, equality of estimated and true expected WTP is not rejected for 89.7% or more when the sample size is 1000. Similarly, equality of estimated preference coefficients and true preference coefficients is not rejected for 88.8% or more. In this study, we find that benefit transfer performs better only in one direction. When the function is estimated at lower scale and transferred to the policy site with higher scale, the transfer error is less in magnitude than those which are estimated at higher scale and transferred to the policy site with lower scale. This study also finds that transfer error is less when the function from the study site having more site substitutes is transferred to the policy site having less site substitutes whenever there is difference in site substitution possibilities. Transfer error is magnified when measurement error is involved in any of the variables. This study do not suggest function transfer whenever the study site's model is missing one of the important variable at the policy site or whenever the data on variables included in study site's model is not available at the policy site for benefit transfer application. This study also suggests the use of large representative sample with sufficient variation to minimize transfer error in benefit transfer. / Master of Science

No / Context: Two-dimensional (2D) video analysis of frontal-plane dynamic knee valgus during common athletic screening tasks has been purported to identify individuals who may be at high risk of suffering knee injuries such as anterior cruciate ligament tear or patellofemoral pain syndrome. Although the validity of 2D video analysis has been studied, the associated reliability and measurement error have not. To assess the reliability and associated measurement error of a 2D video analysis of lower limb dynamic valgus. Design: Reliability study. Participants: 20 recreationally active university students (10 women age 21.5 ± 2.3 y, height 170.1 ± 6.1 cm, weight 66.2 ± 10.2 kg, and 10 men age 22.6 ± 3.1 y, height 177.9 ± 6.0 cm, weight 75.8 ± 7.9 kg). Main Outcome Measurement: Within-day and between-days reliability and measurement-error values of 2D frontal-plane projection angle (FPPA) during common screening tasks. Interventions: Participants performed single-leg squat and drop jump and single-leg landings from a standard 28-cm step with standard 2D digital video camera assessment. Results: Women demonstrated significantly higher FPPA in all tests except the left single-leg squat. Within-day ICCs showed good reliability and ranged from .59 to .88, and between-days ICCs were good to excellent, ranging from .72 to .91. Standard error of measurement and smallest detectable difference values ranged from 2.72° to 3.01° and 7.54° to 8.93°, respectively. Conclusions: 2D FPPA has previously been shown to be valid and has now also been shown to be a reliable measure of lower extremity dynamic knee valgus. Using the measurement error values presented along with previously published normative data, clinicians can now make informed judgments about individual performance and changes in performance resulting from interventions.

Distance sampling is one of the most commonly used methods for estimating density and abundance. Conventional methods are based on the distances of detected animals from the center of point transects or the center line of line transects. These distances are used to model a detection function: the probability of detecting an animal, given its distance from the line or point. The probability of detecting an animal in the covered area is given by the mean value of the detection function with respect to the available distances to be detected. Given this probability, a Horvitz-Thompson- like estimator of abundance for the covered area follows, hence using a model-based framework. Inferences for the wider survey region are justified using the survey design. Conventional distance sampling methods are based on a set of assumptions. In this thesis I present results that extend distance sampling on two fronts. Firstly, estimators are derived for situations in which there is measurement error in the distances. These estimators use information about the measurement error in two ways: (1) a biased estimator based on the contaminated distances is multiplied by an appropriate correction factor, which is a function of the errors (PDF approach), and (2) cast into a likelihood framework that allows parameter estimation in the presence of measurement error (likelihood approach). Secondly, methods are developed that relax the conventional assumption that the distribution of animals is independent of distance from the lines or points (usually guaranteed by appropriate survey design). In particular, the new methods deal with the case where animal density gradients are caused by the use of non-random sampler allocation, for example transects placed along linear features such as roads or streams. This is dealt with separately for line and point transects, and at a later stage an approach for combining the two is presented. A considerable number of simulations and example analysis illustrate the performance of the proposed methods.

Magistro darbe tiriami brandžių medynų tūrio nustatymo metodai. Medynų tūris nustatomas pagal : 1) atrankinio medžių matavimo metodo duomenis (miškotvarkos metu nustatytas medyno tūris), 2) ištisinio medžių matavimo nustatytą tūrį, 3) tūris nustatytas pagal pagamintą medienos produkciją (pridedant biologinės įvairovės bei sėklinių medžių tūrius, taip pat pridedant atliekas pagal „Medžių tūrio struktūros“ lenteles ). Darbo objektas - Tytuvėnų miškų urėdijos, Kelmės krašto IV miškų grupės brandūs medynai. Tikslas – įvertinti kertamų medynų likvidinės medienos tūrio nustatymo tikslumą ir pasitaikančių skirtumų priežastis. Darbo metodai – medienos tūrio paklaidų, gautų lyginant ištisinio medienos matavimo duomenis su miškotvarkos metu nustatytu tūriu ir pagamintos produkcijos duomenimis, analizė. Palyginti skirtingais metodais apskaičiuotą medienos tūrį. Darbo rezultatai: Įvertinus kertamų eglynų tūrį, pagal ištisinį medžių matavimo metodą, gauti rezultatai parodė, kad vidutinis medienos tūris yra 0,7 % didesnis lyginant su miškotvarkos duomenimis (atrankinis medžių matavimo metodas). Medynuose, pagal atskiras medžių rūšis, didžiausi skirtumai pušies 8,7 % ir liepos 8,2 % medžių tūriuose. Įvertinus Tytuvėnų miškų urėdijos brandžius medynus pagal ištisinį medžių matavimo metodą (etalonas) ir pagamintą medienos produkciją (pridedant biologinės įvairovės ir sėklinius medžius, pridedant atliekų tūrį) nustatyta, kad biržėse prikertama daugiau nei planuota, vidutiniškai 0,2 %... [toliau žr. visą tekstą] / In Master thesis investigate mature stand volume determination. Stands must be determined by: a) a selective method for measuring tree data (at the forest stand volume), 2) continuous measurement of the volume of trees, 3) the volume of manufactured wood products (by adding bio-diversity and tree seed volumes, as well as the addition of waste under "Medienos tūrio struktūros” tables.) Object of research - Tytuvėnai forest enterprises Kelmė region IV group mature trees. Aim of research - to assess crossed stand merchantable timber volume and accuracy in common reasons for the differences. Methods of research - the timber volume errors, obtained by comparing the continuous measurement of wood in the forest data set in the volume and output data analysis. Compare the different methods produce timber volume. Results of the research: The assessment of the spruce volume crossed by a continuous method of measuring the trees, the results showed that the average wood volume is 0.7 % higher compared with the forest data (selective tree method). Stands under different tree species, the largest differences between pine 8,7 % and lime 8,2 % tree volumes. The assessment of forest enterprises Tytuvėnai mature stands of trees under the continuous measurement method (standard) and made of wood products (by adding bio-diversity and tree seedling, plus the volume of waste) finds that cut down more than expected, on average 0.2% increase.

O objetivo principal deste trabalho é estudar modelos mistos lineares elípticos em que uma das variáveis explicativas ou covariáveis é medida com erros, sob a abordagem estrutural. O trabalho é apresentado numa notação longitudinal, todavia a covariável medida com erros pode ser observada temporalmente ou como medidas repetidas. Assumimos uma estrutura hierárquica apropriada com distribuição elíptica conjunta para os erros envolvidos, porém a inferência é desenvolvida sob uma abordagem marginal em que consideramos a distribuição marginal da resposta e da variável medida com erros. Procedimentos de influência local em que o esquema de perturbação é escolhido de forma apropriada são desenvolvidos. Um exemplo para motivação é apresentado e analisado através dos procedimentos apresentados neste trabalho. Detalhamos nos apêndices os principais procedimentos necessários para o desenvolvimento do modelo proposto. / The aim of this thesis is to study elliptical linear mixed models in which one of the explanatory variables is subject to measurement error under the structural assumption. The work is presented by assuming a longitudinal structure, however the explanatory variable may be observed along the time or as repeated measures. A joint hierarchical structure is assumed for the elliptical errors, but the inference is made under the marginal structure. The methodology of local influence is applied with the perturbation schemes being selected appropriately. A motivation example is presented and analysed by the procedures developed in this work. All the main derivations for the development of the proposed model are presented in the appendices.

Modelos com erros de medição têm recebido a atenção de vários pesquisadores das mais diversas áreas de conhecimento. O principal objetivo desta dissertação consiste no estudo de um modelo funcional com erros de medição heteroscedásticos na presença de réplicas das observações. O modelo proposto estende resultados encontrados na literatura na medida em que as réplicas são parte do modelo, ao contrário de serem utilizadas para estimação das variâncias, doravante tratadas como conhecidas. Alguns procedimentos de estimação tais como o método de máxima verossimilhança, o método dos momentos e o método de extrapolação da simulação (SIMEX) na versão empírica são apresentados. Além disso, propõe-se o teste da razão de verossimilhanças e o teste de Wald com o objetivo de testar algumas hipóteses de interesse relacionadas aos parâmetros do modelo adotado. O comportamento dos estimadores de alguns parâmetros e das estatísticas propostas (resultados assintóticos) são analisados por meio de um estudo de simulação de Monte Carlo, utilizando-se diferentes números de réplicas. Por fim, a proposta é exemplificada com um conjunto de dados reais. Toda parte computacional foi desenvolvida em linguagem R (R Development Core Team, 2011) / Measurement error models have received the attention of many researchers of several areas of knowledge. The aim of this dissertation is to study a functional heteroscedastic measurement errors model with replicated observations. The proposed model extends results from the literature in that replicas are part of the model, as opposed to being used for estimation of the variances, now treated as known. Some estimation procedures such as maximum likelihood method, the method of moments and the empirical simulation-extrapolation method (SIMEX) are presented. Moreover, it is proposed the likelihood ratio test and Wald test in order to test hypotheses of interest related to the model parameters used. The behavior of the estimators of some parameters and statistics proposed (asymptotic results) are analyzed through Monte Carlo simulation study using different numbers of replicas. Finally, the proposal is illustrated with a real data set. The computational part was developed in R language (R Development Core Team, 2011)

La non-réponse, rencontrée dans la plupart des enquêtes épidémiologiques, est génératrice de biais de sélection (qui, dans ce cas est un biais de non-réponse) lorsqu’elle est liée aux variables d’intérêt. En surveillance épidémiologique, dont un des objectifs est d’estimer des prévalences, on a souvent recours à des enquêtes par sondage. On est alors confronté à la non-réponse totale et on peut utiliser des méthodes issues de la statistique d’enquête pour la corriger. Le biais de non-réponse peut être exprimé comme le produit de l’inverse du taux de réponse et de la covariance entre la probabilité de réponse et la variable d’intérêt. Ainsi, deux types de solution peuvent généralement être envisagés pour diminuer ce biais. La première consiste à chercher à augmenter le taux de réponse au moment de la planification de l’enquête. Cependant, la maximisation du taux de réponse peut entraîner d’autres types de biais, comme des biais de mesure. Dans la seconde, après avoir recueilli les données, on utilise des informations liées a priori aux variables d’intérêt et à la probabilité de réponse, et disponibles à la fois pour les répondants et les non-répondants pour calculer des facteurs correctifs. Cette solution nécessite donc de disposer d’informations sur l'ensemble de l'échantillon tiré au sort (que les personnes aient répondu ou non) ; or ces informations sont en général peu nombreuses. Les possibilités récentes d'accès aux bases médico-administratives (notamment celles de l'assurance maladie) ouvrent de nouvelles perspectives sur cet aspect.Les objectifs de ce travail, qui sont centrés sur les biais de non-réponse, étaient d’étudier l’apport de données supplémentaires (enquête complémentaire auprès de non-répondants et bases médico-administratives) et de discuter l’influence du taux de réponse sur l’erreur de non-réponse et l’erreur de mesure.L'analyse était centrée sur la surveillance épidémiologique des risques professionnels via l’exploitation des données de la phase pilote de la cohorte Coset-MSA à l’inclusion. Dans cette enquête, en plus des données recueillies par questionnaire (enquête initiale et enquête complémentaire auprès de non-répondants), des informations auxiliaires issues de bases médico-administratives (SNIIR-AM et MSA) étaient disponibles pour les répondants mais aussi pour les non-répondants à l’enquête par questionnaire.Les résultats montrent que les données de l’enquête initiale, qui présentait un taux de réponse de 24%, corrigées pour la non-réponse avec des informations auxiliaires directement liées à la thématique de l’enquête (la santé et le travail) fournissent des estimations de prévalence en général proches de celles obtenues grâce à la combinaison des données de l’enquête initiale et de l’enquête complémentaire (dont le taux de réponse atteignait 63%) après correction de la non réponse par ces mêmes informations auxiliaires. La recherche d'un taux de réponse maximal à l’aide d’une enquête complémentaire n’apparait donc pas nécessaire pour diminuer le biais de non réponse. Cette étude a néanmoins mis en avant l’existence de potentiels biais de mesure plus importants pour l’enquête initiale que pour l’enquête complémentaire. L’étude spécifique du compromis entre erreur de non-réponse et erreur de mesure montre que, pour les variables qui ont pu être étudiées, après correction de la non-réponse, la somme de l’erreur de non-réponse de l’erreur de mesure est équivalente dans l’enquête initiale et dans les enquêtes combinées (enquête initiale et complémentaire).Ce travail a montré l’intérêt des bases médico-administratives pour diminuer l’erreur de non-réponse et étudier les erreurs de mesure dans une enquête de surveillance épidémiologique. / Nonresponse occurs in most epidemiologic surveys and may generate selection bias (which is, in this case, a nonresponse bias) when it is linked to outcome variables. In epidemiologic surveillance, whose one of the purpose is to estimate prevalences, it is usual to use survey sampling. In this case, unit nonresponse occurs and it is possible to use methods coming from survey sampling to correct for nonresponse. Nonresponse bias can be expressed as the product of the inverse of the response rate and the covariance between the probability of response and the outcome variable. Thus, two options are available to reduce the effect of nonresponse. The first is to increase the response rate by developing appropriate strategies at the study design phase. However, the maximization of the response rate can prompt other kinds of bias, such as measurement bias. In the second option, after data collection, information associated with both nonresponse and the outcome variable, and available for both respondents and nonrespondents, can be used to calculate corrective factors. This solution requires having information on the complete random sample (respondents and nonrespondents); but this information is rarely sufficient. Recent possibilities to access administrative databases (particularly those pertaining to health insurance) offer new perspectives on this aspect.The objectives of this work focused on the nonresponse bias were to study the contribution of supplementary data (administrative databases and complementary survey among nonrespondents) and to discuss the influence of the response rate on the nonresponse error and the measurement error. The analyses focused on occupational health epidemiologic surveillance, using data (at inclusion) from the Coset-MSA cohort pilot study. In this study, in addition to the data collected by questionnaire (initial and complementary survey among nonrespondents), auxiliary information from health and occupational administrative databases was available for both respondents and nonrespondents.Results show that the data from the initial survey (response rate : 24%), corrected for nonresponse with information directly linked to the study subject (health and work) produce estimations of prevalence close to those obtained by combining data from the initial survey and the complementary survey (response rate : 63%), after nonresponse adjustment on the same auxiliary information. Using a complementary survey to attain a maximal response rate does not seem to be necessary in order to decrease nonresponse bias. Nevertheless, this study highlights potential measurement bias which could be more consequential for the initial survey than for the complementary survey. The specific study of the trade-off between nonresponse error and measurement error shows that, for the studied variables and after correction for nonresponse, the sum of the nonresponse error and the measurement error is equivalent in the initial survey and in the combined surveys (initial plus complementary survey). This work illustrated the potential of administrative databases for decreasing the nonresponse error and for evaluating measurement error in an epidemiologic surveillance survey.

O objetivo principal deste trabalho é estudar modelos mistos lineares elípticos em que uma das variáveis explicativas ou covariáveis é medida com erros, sob a abordagem estrutural. O trabalho é apresentado numa notação longitudinal, todavia a covariável medida com erros pode ser observada temporalmente ou como medidas repetidas. Assumimos uma estrutura hierárquica apropriada com distribuição elíptica conjunta para os erros envolvidos, porém a inferência é desenvolvida sob uma abordagem marginal em que consideramos a distribuição marginal da resposta e da variável medida com erros. Procedimentos de influência local em que o esquema de perturbação é escolhido de forma apropriada são desenvolvidos. Um exemplo para motivação é apresentado e analisado através dos procedimentos apresentados neste trabalho. Detalhamos nos apêndices os principais procedimentos necessários para o desenvolvimento do modelo proposto. / The aim of this thesis is to study elliptical linear mixed models in which one of the explanatory variables is subject to measurement error under the structural assumption. The work is presented by assuming a longitudinal structure, however the explanatory variable may be observed along the time or as repeated measures. A joint hierarchical structure is assumed for the elliptical errors, but the inference is made under the marginal structure. The methodology of local influence is applied with the perturbation schemes being selected appropriately. A motivation example is presented and analysed by the procedures developed in this work. All the main derivations for the development of the proposed model are presented in the appendices.

Modelos de regressão com resposta binária são utilizados na solução de problemas nas mais diversas áreas. Neste trabalho enfocamos dois problemas comuns em certos conjuntos de dados e que requerem técnicas apropriadas que forneçam inferências satisfatórias. Primeiro, em certas aplicações uma mesma unidade amostral é utilizada mais de uma vez, acarretando respostas positivamente correlacionadas, responsáveis por uma variância na variável resposta superior ao que comporta a distribuição binomial, fenômeno conhecido como sobredispersão. Por outro lado, também encontramos situações em que a variável explicativa contém erros de medição. É sabido que utilizar técnicas que desconsideram esses erros conduz a resultados inadequados (estimadores viesados e inconsistentes, por exemplo). Considerando um modelo com resposta binária, utilizaremos a distribuição beta-binomial para representar a sobredispersão. Os métodos de máxima verossimilhança, SIMEX, calibração da regressão e máxima pseudo-verossimilhança foram usados na estimação dos parâmetros do modelo, que são comparados através de um estudo de simulação. O estudo de simulação sugere que os métodos de máxima verossimilhança e calibração da regressão são melhores no sentido de correção do viés, especialmente para amostras de tamanho 50 e 100. Também estudaremos testes de hipóteses assintóticos (como razão de verossimilhanças, Wald e escore) a fim de testar hipóteses de interesse. Apresentaremos também um exemplo com dados reais / Regression models with binary response are used for solving problems in several areas. In this work we approach two common problems in some data sets and they need appropriate techniques to achieve satisfactory inference. First, in some applications, the same sample unity is utilized more than once, bringing positively correlated responses, which are responsible for the response variable variance be greater than an assumption binomial distribution, phenomenon known as overdispersion. On the other hand, also we find situations where the explanatory variable has measurement errors. It is known that the use of techniques which ignores these measurement errors brings inadequate results (e. g., biased and inconsistent estimators). Taking a model with binary response, we will use a beta-binomial distribution for modeling the overdispersion. The methods of maximum likelihood, SIMEX, regression calibration and maximum pseudo-likelihood were used in the estimation of the parameters, which are compared through a simulation study. The simulation studies suggest that the maximum likelihood and regression calibration methods are better for bias correcting, especially for larger sample size. Likelihood ratio, Wald and score statistics are used in order to test hypothesis of interest. We will illustrate the techniques with an application to a real data set