Studies suggest that nearly two-thirds of women fake or have faked orgasm, yet few researchers have explicitly examined this phenomenon. Previous studies have identified some group differences between women who fake orgasm and those who do not on dimensions of sexual experience, emotion regulation, intimacy, relationship status, and sexual functioning. To date, research into this phenomenon has relied solely on variable-centered analyses (e.g., exploratory factor analysis, correlation, and regression). This study used a person-centered approach (i.e., latent class analysis; LCA) to explore differences in women's motives across individuals, using scores from the Faking Orgasm Scale. A 5-class model was determined to be most interpretable and the best fitting to the data. Classes included low, moderate, and high frequency faking orgasm, partner-focused faking orgasm, and pleasure-focused faking orgasm. These classes were then compared on dimensions of sexual functioning, intimacy, and emotion regulation, as well as demographic variables (e.g., age, length of relationship, number of sexual partners). Significant differences were found in sexual desire, sexual activity, and orgasmic consistency, but not in sexual satisfaction. Significant differences were also evidenced in intimacy, general level of emotion dysregulation, and across various dimensions of emotion regulation. No differences across classes were revealed on age, length of relationship, or number of sexual partners. These findings can serve as the foundation for further exploration into understanding women's various styles of interacting sexually with a partner and may have implications for couples therapy, sex therapy, and individual interventions for women struggling with physical and/or emotional intimacy with a partner. / Psychology

A multitude of research demonstrates that ADHD is associated with negative psychological correlates and outcomes among children, such as academic difficulties and peer relationship problems. Youth with ADHD also experience high rates of comorbidity or co-occurring conditions, including mood, anxiety, oppositional defiant, and conduct disorders. However, few studies have investigated the development of co-occurring psychological symptoms among youth with ADHD over time and across different developmental periods. Shared risk factors likely contribute to the development of ODD, CD, anxiety, and depression among youth with ADHD. Emotion regulation and parenting style may confer risk or resilience for the development of co-occurring symptoms, but research is wanting. The current study examined an existing sample of youth who were recruited at age 10-12 and were followed at age 12-14 and 16. Analyses aimed to (a) identify subgroups of youth varying in type and levels of ADHD and co-occurring symptoms at three different time points using latent class analyses, (b) examine stability of membership and transitions to classes that differ in levels of ADHD and co-occurring symptoms using latent transition analyses, and (c) investigate emotion regulation and parenting style as predictors of stability and transitions among classes. Results revealed different patterns of ADHD and co-occurring symptoms, including a Low Symptoms class at each time point. Classes of youth with ADHD+Externalizing problems and ADHD+Internalizing problems emerged at ages 10-12 and 12-14. At age 16, two classes with qualitatively and quantitatively different externalizing and internalizing symptoms were identified. Latent transition analyses revealed transitions into the Low Symptoms class from each time point, but also stability and transitions to other symptomatic classes. Predictor analyses indicated that emotion regulation and parenting style were associated with transitions among and stability within classes, but findings were dependent on whether classes were defined primarily by co-occurring externalizing or internalizing symptoms. Results of the present study indicate that children with ADHD are likely to exhibit a range of psychological symptoms, but the frequency and quality of co-occurring symptoms may change over time. Emotion regulation and parenting may be potential targets for enhanced interventions among youth with ADHD with and without co-occurring symptoms. / Psychology

Labeling is a product differentiation mechanism which has increased in prevalence across many markets. This study investigated the potential for a labeling program applied in ornamental plant sales, given key ongoing issues affecting ornamental plant producers: irrigation water use and plant disease. Our research investigated how to better understand the market for plants certified as disease free and/or produced using water conservation techniques through segmenting the market by consumers' environmental preferences. Latent class analysis was conducted using choice modeling survey results and respondent scores on the New Environmental Paradigm scale. The results show that when accounting for environmental preferences, consumers can be grouped into two market segments. Relative to each other, these segments are considered: price sensitive and attribute sensitive. Our research also investigated market segments' preferences for multiple certifying authorities. The results strongly suggest that consumers of either segment do not have a preference for any particular certifying authority. / Master of Science

Insufficient knowledge of residential preferences represents a major obstacle to achieving residential satisfaction and quality of life. This obstacle is even greater in the case of transit-oriented developments (TODs), as their success depends, in part, on the degree to which people's preferences are consistent with their residential environments. This study employed a visual choice experiment, which combines the benefits of visual preference surveys and discrete choice experiments, to elicit residential preference for TODs in Riyadh, Saudi Arabia, before the opening of its citywide public transportation system. Using a seemingly homogeneous sample of participants, the analysis incorporated three analytical methods to elicit residential preference: a multinomial logit model, a mixed logit model, and a latent class model. The results indicated the presence of preference heterogeneity and the emergence of four lifestyle classes that could explain and predict residential preference patterns. People with similar sociodemographic characteristics may have different lifestyles based on their choice behavior, marital status, and public transit attitudes. Additionally, the results showed a strong preference for low-density housing, even among those who favor living in a TOD; however, increasing density could be mitigated through the presence of other TOD attributes. The findings of this research point to the diversity of residential preferences and suggest that providing a variety of residential environments increases the likelihood that people will find their preferred environment. Additionally, planning efforts to convert all developments near transit, particularly in suburban locations, to TODs might be unsuitable in cities where public transportation has been introduced only recently. Instead, deferring TOD conversion efforts until public transportation and its use are mature may attract people to live near transit and encourage the gradual development of transit affinity in residents who may otherwise reject TOD living completely. Lastly, the successful application of a visual choice experiment in this research opens up a variety of potential analytical methods that are used commonly in other fields and have the potential to move visual preference research into the realm of robust empirical investigation. / Ph. D. / The work of urban planners, urban designers, architects, and policy makers centers on improving the built environment and increasing the quality of people’s lives. However, their work entails making decisions that are not always in tandem with people’s preferences (e.g., increasing housing density, proposing a mix of land uses in residential neighborhoods, introducing public transportation close to where people live and work, to name a few). Due to the uncertainty surrounding people’s acceptance of modifications of the built environment, especially when it entails introducing residential attributes for the first time, this dissertation focused on 1) assessing residential preference near public transportation nodes in Riyadh, Saudi Arabia before operation of the public transportation system, and 2) assessing the extent to which advanced analytical methods are capable of providing a better understanding of residential preference differences among a seemingly homogenous sample of participants. The work in this dissertation was motivated by the increasing use of manipulated images in choice tasks, where participants are presented with multiple images, each depicting a residential scenario, as bundles to choose from, and their choice patterns then recorded and analyzed. The results showed that among the relatively homogenous sample of participants that was recruited, four significant residential preference patterns have emerged, which could be used to describe and predict residential preference and choice with great accuracy. This dissertation laid out several policy implications that could be useful in providing a built environment that matches with what people want. It also provided research implications and suggestions on the use of visual choice experiments for urban planners and designers that are well-developed in other fields of inquiry.

The Outcome Questionnaire (OQ-45; Lambert et al., 1996) has been widely employed as a psychotherapy outcome monitoring measure following research findings that support various aspects of its validity and sensitivity to change. Despite its broad usage in both clinical and research settings, some of its psychometric properties are not definite. The three subscales of the OQ-45 are designed to measure three distinct, but related, aspects of psychological functioning. However, neither the one- nor three-factor models have been supported by previous research. Likewise, the results of the current study supported neither of those factor structures. It was suspected that heterogeneity in data might have led to the lack of the confirmatory factor analysis model fit. Therefore, factor mixture modeling (FMM), a combination of confirmatory factor analysis and latent class analysis, was employed to investigate potential heterogeneity of the data. Among the series of factor mixture models with varying numbers of classes that were fitted, the two-class, unconditional FMM based on the revised three-factor solution was decided to best describe the data under analysis. Although three covariates of clinical status, sex, and race were selected as known sources of heterogeneity and incorporated into the FMMs (i.e., conditional model), the findings were contradictory to expectations. The implications of these findings in counseling were discussed in terms of aggregating OQ-45 scores and its score interpretation. Furthermore, this study demonstrates the process involved and dilemmas encountered in choosing the best fitting FMM. There is currently no criterion for assessing individual model fit. Instead, models’ fit are compared using various information criteria (IC). And, as was found in the current study, these ICs are frequently contradictory. Thus, the process of identifying the best fitting model cannot rest solely on fit indices but must also depend on interpretation of models and consideration of the ultimate use of the results. In the current study, consideration of transition matrices and the pattern of latent means across classes contributed as much to model selection as fit index interpretation. / text

Objectives: Adherence to psychotropic medication is poor among individuals with bipolar disorder (BD). To understand treatment experiences and associated adherence among these individuals, we developed a novel construct of Clinical Net Benefit (CNB) using psychiatric symptoms, adverse effects and overall functioning assessments. We tested whether adherence differed across classes of CNB, whether individuals transitioned between classes over time, and whether these transitions were differentially associated with adherence. Methods: Data come from individuals aged 18+ during five years of the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD). Latent class analysis identified groups of CNB. Latent transition analysis determined probabilities of transitioning between classes over time. Adherence was defined as taking 75%+ of medications as prescribed. Associations between CNB and adherence were tested using multiple logistic regression adjusting for sociodemographic characteristics. Results: Five classes of CNB were identified during the first two years (high, moderately high, moderate, moderately low, low), and four classes (removing moderately high) during the last three years. Adherence did not differ across classes or time points. Medication regimens differed by class; those with higher CNB taking fewer medications had lower odds of adherence while those with lower CNB taking more medications had higher odds of adherence compared with monotherapy. Probability of transitioning from higher to lower CNB, and lower to higher CNB was greatest over time. Conclusions: CNB is heterogeneous in individuals treated for BD, and movement between classes is not uncommon. Understanding why individuals adhere despite suboptimal CNB may provide novel insights into aspects influencing adherence.

In model-based clustering mixture models are used to group data points into clusters. A useful concept introduced for Gaussian mixtures by Malsiner Walli et al. (Stat Comput 26:303-324, 2016) are sparse finite mixtures, where the prior distribution on the weight distribution of a mixture with K components is chosen in such a way that a priori the number of clusters in the data is random and is allowed to be smaller than K with high probability. The number of clusters is then inferred a posteriori from the data. The present paper makes the following contributions in the context of sparse finite mixture modelling. First, it is illustrated that the concept of sparse finite mixture is very generic and easily extended to cluster various types of non-Gaussian data, in particular discrete data and continuous multivariate data arising from non-Gaussian clusters. Second, sparse finite mixtures are compared to Dirichlet process mixtures with respect to their ability to identify the number of clusters. For both model classes, a random hyper prior is considered for the parameters determining the weight distribution. By suitable matching of these priors, it is shown that the choice of this hyper prior is far more influential on the cluster solution than whether a sparse finite mixture or a Dirichlet process mixture is taken into consideration.

A leishmaniose visceral americana (LVA) é uma doença em expansão no Brasil, para a qual se dispõem de poucas, e aparentemente ineficientes, estratégias de controle. Um dos grandes problemas para a contenção da leishmaniose visceral americana é a falta de um método acurado de identificação dos cães infectados, considerados os principais reservatórios da doença no meio urbano. Neste sentido, a caracterização de marcadores clínico-laboratoriais da infecção neste reservatório e a avaliação mais adequada do desempenho de testes para diagnóstico da infecção podem contribuir para aumentar a efetividade das estratégias de controle da LVA. Com isso, o presente estudo tem dois objetivos principais: (1) desenvolver e validar um modelo de predição para o parasitismo por Leishmania chagasi em cães, baseado em resultados de testes sorológicos e sinais clínicos e (2) avaliar a sensibilidade e especificidade de critérios clínicos, sorológicos e parasitológicos para detecção de infecção canina por L. chagasi mediante análise de classe latente. O primeiro objetivo foi desenvolvido a partir de estudo em que foram obtidos dados de exames clínico, sorológico e parasitológico de todos os cães, suspeitos ou não de LVA, atendidos no Hospital Veterinário Universitário da Universidade Federal do Piauí (HVU-UFPI), em Teresina, nos anos de 2003 e 2004, totalizando 1412 animais. Modelos de regressão logística foram construídos com os animais atendidos em 2003 com a finalidade de desenvolver um modelo preditivo para o parasitismo com base nos sinais clínicos e resultados de sorologia por Imunofluorescência Indireta (IFI). Este modelo foi validado nos cães atendidos no hospital em 2004. Para a avaliação da área abaixo da curva ROC (auROC), sensibilidade, especificidade, valores preditivos positivo (VPP), valores preditivos negativo (VPN) e acurácia global, foram criados três modelos: um somente baseado nas variáveis clínicas, outro considerando somente o resultado sorológico e um último considerando conjuntamente a clínica e a sorologia. Dentre os três, o último modelo apresentou o melhor desempenho (auROC=90,1%, sensibilidade=82,4%, especificidade=81,6%, VPP=73,4%, VPN=88,2% e acurácia global=81,9%). Conclui-se que o uso de modelos preditivos baseados em critérios clínicos e sorológicos para o diagnóstico da leishmaniose visceral canina pode ser de utilidade no processo de avaliação da infecção canina, promovendo maior agilidade na contenção destes animais com a finalidade de reduzir os níveis de transmissão. O segundo objetivo foi desenvolvido por meio de um estudo transversal com 715 cães de idade entre 1 mês e 13 anos, com raça variada avaliados por clínicos veterinários no HVU-UFPI, no período de janeiro a dezembro de 2003. As sensibilidades e especificidades de critérios clínicos, sorológicos e parasitológicos para detecção de infecção canina por Leishmania chagasi foram estimadas por meio de análise de classe latente, considerando quatro modelos de testes e diferentes pontos de corte. As melhores sensibilidades estimadas para os critérios clínico, sorológico e parasitológico foram de 60%, 95% e 66%, respectivamente. Já as melhores especificidades estimadas para os critérios clínico, sorológico e parasitológico foram de 77%, 90% e 100%, respectivamente. Conclui-se que o uso do exame parasitológico como padrão-ouro para validação de testes diagnósticos não é apropriado e que os indicadores de acurácia dos testes avaliados são insuficientes e não justificam que eles sejam usados isoladamente para diagnóstico da infecção com a finalidade de controle da doença. / American visceral leishmaniasis (AVL) is an expanding disease in Brazil, for which few, and apparently inefficient, control strategies are available. A major problem for the containment of visceral leishmaniasis is the lack of an accurate test for the identification of infected dogs, which are considered the main reservoirs of the disease in urban areas. In this sense, the characterization of clinical and laboratory markers of the infection in this reservoir, as well as, a more appropriate assessment of the performance of tests for the diagnosis of infection, might increase the effectiveness of control strategies for AVL. Thus, this study has two main objectives: (1) to develop and validate a prediction model for parasitism by Leishmania chagasi in dogs, based on the results of serological tests and clinical signs and (2) to evaluate the sensitivity and specificity of a clinical criterion, and of parasitological and serological tests for canine infection by L. chagasi using latent class analysis. The first goal was developed from a study in which clinical, serological and parasitological data were obtained for all dogs, suspicious or not to AVL, admitted at the Veterinary Hospital at the Federal University of Piauí, Teresina, in the years of 2003 and 2004, totaling 1412 animals. Logistic regression models were constructed with the animals admitted in 2003 with the aim of developing a predictive model for parasitism based on clinical signs and results of serology by indirect immunofluorescence (IIF). This model was validated in dogs admitted at the hospital in 2004. To evaluate the area under the ROC curve (AuROC), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and overall accuracy, three models were developed: one based only on clinical variables, other only with the serological results and a final model based on both the clinical and serological data. Among the three, the last model showed the best performance (AuROC=90.1%, sensitivity 82.4%, specificity=81.6%, PPV=73.4% NPV=88.2% and overall accuracy=81.9%). It is concluded that the use of predictive models based on clinical and serological data for diagnosis of canine visceral leishmaniasis might be useful in the evaluation of canine infection, allowing the anticipation of ontainment of these animals in order to reduce transmission levels. The second goal was developed through a cross-sectional study of 715 dogs aged between 1 month and 13 years, with varied races evaluated by veterinarians at VUH-UFPI in the period January to December 2003. The sensitivities and specificities of clinical, parasitological and serological tests for detection of canine infection by Leishmania chagasi were estimated using latent class analysis, considering four types of models and different cutoffs. The best sensitivity estimates for the clinical, serological and parasitological tests were 60%, 95% and 66% respectively. The best estimates for the specificity of clinical, serological and parasitological tests were 77%, 90% and 100% respectively. It is concluded that the use of parasitological assays as the gold standard for validation of diagnostic tests is not appropriate and that the indicators of accuracy of the tests evaluated are insufficient to justify that they are used alone for diagnosis of infection in order to control the disease.

Objetivo: Identificar principais componentes da síndrome metabólica e características associadas, bem como identificar os perfis de anormalidades e sua variabilidade étnica. Métodos: Estudo transversal envolvendo 14544 participantes da linha de base do Estudo Longitudinal de Saúde do Adulto (ELSA-Brasil). Com idade entre 35 e 74 anos de diferentes regiões do Brasil. Foi feita uma análise fatorial exploratória em variáveis associadas à síndrome metabólica, com uma análise de agrupamento dos participantes em função de seus escores fatoriais. Paralelamente, análise de classes latentes foi feita em toda a amostra, após categorização das variáveis. As proporções das classes foram avaliadas em cada estrato de raça/cor dos participantes. Resultados: Na amostra ELSA observou-se três fatores que explicam 97,7% da variabilidade das variáveis associadas à síndrome: componentes da síndrome metabólica e inflamação; hipertensão; enzimas hepáticas. Na análise de classes latentes observaram-se seis perfis de manifestação dos componentes síndrome, sendo que o perfil com maior prevalência no estudo é de pessoas com sobrepeso e hiperglicemia, mas com probabilidade menor de apresentar hipertensão. Nesta classe, a prevalência da síndrome metabólica (definida pelo critério conjunto) é de 42%. Esta classe é mais comum entre os indígenas do que nas demais categorias de raça/cor. Conclusão: A síndrome metabólica se manifesta de formas distintas na população. A investigação da associação destas manifestações com desfechos de interesse poderia aprofundar o conhecimento sobre a síndrome metabólica. / Objective: identify key components of the metabolic syndrome and associated features, as well as identify abnormalities groups and its ethnic variability. Methods: Cross-sectional study involving 14544 baseline participants of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil), aged between 35 and 74 years, from different country regions. A exploratory factorial analysis was done on selected variables associated with the metabolic syndrome, with a cluster analysis done on the participants factor scores. At the same time, a latent class analysis was done on all participants and on the subset that had metabolic syndrome diagnosis, after the variables were categorized. The proportions of classes were evaluated in each stratum of race/color of the participants. Results: We observed 3 factors on the ELSA sample. They explain 97.7% of the variability of the variables associates with the metabolic syndrome: the metabolic syndrome and inflammation components; hypertension, markers of the non-alcoholic fatty liver disease. In the latent class analysis, we observed 6 classes of metabolic syndrome expression. The proportions of classes were evaluated in each stratum of race/color of the participants. The most prevalent class was of overweight and hiperglicemic subjects, with lower probability of having hipertension. In this class, the metabolic syndrome prevalence is of 42%. This class is more common in indians than in other groups of race/color. Conclusion: The metabolic syndrome is manifested in different ways in the population. The research of the association of these different manifestations with selected outcomes could further the current knowledge on the metabolic syndrome.

A leishmaniose visceral americana (LVA) é uma doença em expansão no Brasil, para a qual se dispõem de poucas, e aparentemente ineficientes, estratégias de controle. Um dos grandes problemas para a contenção da leishmaniose visceral americana é a falta de um método acurado de identificação dos cães infectados, considerados os principais reservatórios da doença no meio urbano. Neste sentido, a caracterização de marcadores clínico-laboratoriais da infecção neste reservatório e a avaliação mais adequada do desempenho de testes para diagnóstico da infecção podem contribuir para aumentar a efetividade das estratégias de controle da LVA. Com isso, o presente estudo tem dois objetivos principais: (1) desenvolver e validar um modelo de predição para o parasitismo por Leishmania chagasi em cães, baseado em resultados de testes sorológicos e sinais clínicos e (2) avaliar a sensibilidade e especificidade de critérios clínicos, sorológicos e parasitológicos para detecção de infecção canina por L. chagasi mediante análise de classe latente. O primeiro objetivo foi desenvolvido a partir de estudo em que foram obtidos dados de exames clínico, sorológico e parasitológico de todos os cães, suspeitos ou não de LVA, atendidos no Hospital Veterinário Universitário da Universidade Federal do Piauí (HVU-UFPI), em Teresina, nos anos de 2003 e 2004, totalizando 1412 animais. Modelos de regressão logística foram construídos com os animais atendidos em 2003 com a finalidade de desenvolver um modelo preditivo para o parasitismo com base nos sinais clínicos e resultados de sorologia por Imunofluorescência Indireta (IFI). Este modelo foi validado nos cães atendidos no hospital em 2004. Para a avaliação da área abaixo da curva ROC (auROC), sensibilidade, especificidade, valores preditivos positivo (VPP), valores preditivos negativo (VPN) e acurácia global, foram criados três modelos: um somente baseado nas variáveis clínicas, outro considerando somente o resultado sorológico e um último considerando conjuntamente a clínica e a sorologia. Dentre os três, o último modelo apresentou o melhor desempenho (auROC=90,1%, sensibilidade=82,4%, especificidade=81,6%, VPP=73,4%, VPN=88,2% e acurácia global=81,9%). Conclui-se que o uso de modelos preditivos baseados em critérios clínicos e sorológicos para o diagnóstico da leishmaniose visceral canina pode ser de utilidade no processo de avaliação da infecção canina, promovendo maior agilidade na contenção destes animais com a finalidade de reduzir os níveis de transmissão. O segundo objetivo foi desenvolvido por meio de um estudo transversal com 715 cães de idade entre 1 mês e 13 anos, com raça variada avaliados por clínicos veterinários no HVU-UFPI, no período de janeiro a dezembro de 2003. As sensibilidades e especificidades de critérios clínicos, sorológicos e parasitológicos para detecção de infecção canina por Leishmania chagasi foram estimadas por meio de análise de classe latente, considerando quatro modelos de testes e diferentes pontos de corte. As melhores sensibilidades estimadas para os critérios clínico, sorológico e parasitológico foram de 60%, 95% e 66%, respectivamente. Já as melhores especificidades estimadas para os critérios clínico, sorológico e parasitológico foram de 77%, 90% e 100%, respectivamente. Conclui-se que o uso do exame parasitológico como padrão-ouro para validação de testes diagnósticos não é apropriado e que os indicadores de acurácia dos testes avaliados são insuficientes e não justificam que eles sejam usados isoladamente para diagnóstico da infecção com a finalidade de controle da doença. / American visceral leishmaniasis (AVL) is an expanding disease in Brazil, for which few, and apparently inefficient, control strategies are available. A major problem for the containment of visceral leishmaniasis is the lack of an accurate test for the identification of infected dogs, which are considered the main reservoirs of the disease in urban areas. In this sense, the characterization of clinical and laboratory markers of the infection in this reservoir, as well as, a more appropriate assessment of the performance of tests for the diagnosis of infection, might increase the effectiveness of control strategies for AVL. Thus, this study has two main objectives: (1) to develop and validate a prediction model for parasitism by Leishmania chagasi in dogs, based on the results of serological tests and clinical signs and (2) to evaluate the sensitivity and specificity of a clinical criterion, and of parasitological and serological tests for canine infection by L. chagasi using latent class analysis. The first goal was developed from a study in which clinical, serological and parasitological data were obtained for all dogs, suspicious or not to AVL, admitted at the Veterinary Hospital at the Federal University of Piauí, Teresina, in the years of 2003 and 2004, totaling 1412 animals. Logistic regression models were constructed with the animals admitted in 2003 with the aim of developing a predictive model for parasitism based on clinical signs and results of serology by indirect immunofluorescence (IIF). This model was validated in dogs admitted at the hospital in 2004. To evaluate the area under the ROC curve (AuROC), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and overall accuracy, three models were developed: one based only on clinical variables, other only with the serological results and a final model based on both the clinical and serological data. Among the three, the last model showed the best performance (AuROC=90.1%, sensitivity 82.4%, specificity=81.6%, PPV=73.4% NPV=88.2% and overall accuracy=81.9%). It is concluded that the use of predictive models based on clinical and serological data for diagnosis of canine visceral leishmaniasis might be useful in the evaluation of canine infection, allowing the anticipation of ontainment of these animals in order to reduce transmission levels. The second goal was developed through a cross-sectional study of 715 dogs aged between 1 month and 13 years, with varied races evaluated by veterinarians at VUH-UFPI in the period January to December 2003. The sensitivities and specificities of clinical, parasitological and serological tests for detection of canine infection by Leishmania chagasi were estimated using latent class analysis, considering four types of models and different cutoffs. The best sensitivity estimates for the clinical, serological and parasitological tests were 60%, 95% and 66% respectively. The best estimates for the specificity of clinical, serological and parasitological tests were 77%, 90% and 100% respectively. It is concluded that the use of parasitological assays as the gold standard for validation of diagnostic tests is not appropriate and that the indicators of accuracy of the tests evaluated are insufficient to justify that they are used alone for diagnosis of infection in order to control the disease.