Bai Yun. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (leaves 34-36). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- The Analysis of a Two-Level SEM with Group Specific Variables in LISREL --- p.4 / Chapter 2.1 --- The Model --- p.4 / Chapter 2.2 --- An Augmented Model --- p.5 / Chapter 2.3 --- Implementation in LISREL --- p.7 / Chapter 2.4 --- Simulation --- p.9 / Chapter 2.4.1 --- The Simulation Design --- p.9 / Chapter 2.4.2 --- Methods of Evaluation --- p.10 / Chapter 2.4.3 --- Simulation Results --- p.12 / Chapter 2.5 --- A Comparison to Mplus --- p.14 / Chapter 2.6 --- Empirical Demonstration: Multi-source Performance Appraisals --- p.14 / Chapter 3 --- Implementing Two level SEM with Cross-level Covariance Structures in Mx --- p.16 / Chapter 3.1 --- Two level Model Specifications with a Cross-level Covariance Structure --- p.17 / Chapter 3.2 --- An Illustrative Example --- p.20 / Chapter 3.3 --- Mx Simulation Design --- p.22 / Chapter 3.4 --- Simulation Results --- p.23 / Chapter 3.4.1 --- Accuracy of Parameter Estimates --- p.23 / Chapter 3.4.2 --- Accuracy of Standard Error Estimates --- p.24 / Chapter 3.4.3 --- Distribution of Goodness-of-fit Statistics --- p.24 / Chapter 3.5 --- Enlarged Mx Model --- p.24 / Chapter 3.5.1 --- Mx Model with Enlarged Xgi --- p.25 / Chapter 3.5.2 --- Mx Model with Enlarged Ng --- p.26 / Chapter 4 --- LISREL Sampling --- p.27 / Chapter 4.1 --- LISREL Sampling Simulation Design --- p.27 / Chapter 4.2 --- Simulation Results --- p.28 / Chapter 4.2.1 --- Accuracy of Parameter Estimates --- p.29 / Chapter 4.2.2 --- Accuracy of Standard Error Estimates --- p.30 / Chapter 4.2.3 --- Distribution of Goodness-of-fit Statistics --- p.30 / Chapter 5 --- Discussion --- p.31 / Appendices --- p.37 / Appendix 1 LISREL Sample Program --- p.37 / Appendix 2 LISREL Syntax for an ALL-Y Model --- p.38 / Appendix 3 LISREL Data Set Up --- p.39 / Appendix 4 Mx Sample Program --- p.40 / List of Figures / Chapter 1 --- The Augmented Two-level Model --- p.41 / Chapter 2 --- Results of the Performance Appraisal Example --- p.42 / Chapter 3 --- Two-level Model with a Cross-level Structure --- p.43 / Chapter 4 --- QQ-plot for P1-P6 --- p.44 / Chapter 5 --- QQ-plot for M1-M6 --- p.45 / List of Tables / Chapter 1 --- Simulation Conditions Associated with Each Pattern --- p.46 / Chapter 2 --- Simulation Results: Accuracy of Parameter Estimates --- p.47 / Chapter 3 --- Simulation Results: Precision of Standard Error Estimates --- p.48 / Chapter 4 --- Simulation Results: The Goodness-of-fit(GOF) Statistics --- p.49 / Chapter 5 --- Analysis of the Performance Appraisal Example --- p.49 / Chapter 6 --- Simulation Results: Mplus vs. LISREL-Parameter Estimates(l) --- p.50 / Chapter 7 --- Simulation Results: Mplus vs. LISREL-Parameter Estimates(2) --- p.51 / Chapter 8 --- Simulation Results: Mplus vs. LISREL-SE Estimates (Ratio) --- p.52 / Chapter 9 --- Simulation Results: Mplus vs. LISREL-GOF Statistics --- p.53 / Chapter 10 --- Mx Illustrative Example Results --- p.53 / Chapter 11 --- Mx Simulation Patterns --- p.53 / Chapter 12 --- Mx Simulation Results: Accuracy of Parameter Estimates --- p.54 / Chapter 13 --- Mx Simulation Results: MARB for Parameter and S.E. Estimates --- p.54 / Chapter 14 --- Mx Simulation Results: Goodness-of-fit Statistics --- p.55 / Chapter 15 --- Mx Simulation Results for M5 --- p.55 / Chapter 16 --- Mx Simulation Results for M5 and M6: Goodness-of-fit Statistics --- p.56 / Chapter 17 --- Mx Simulation Results for M6 --- p.56 / Chapter 18 --- LISREL Sampling: Simulation Patterns --- p.56 / Chapter 19 --- LISREL Sampling: Simulation Results for LI to L3 --- p.57 / Chapter 20 --- LISREL Sampling: Simulation Results for L4 to L6 --- p.58 / Chapter 21 --- LISREL Sampling: MARB for Parameter and S.E. Estimates --- p.59 / Chapter 22 --- LISREL Sampling: Goodness-of-fit Statistics --- p.59

As increasing emphases are placed on the importance of a muscular male physique in Westernized culture, more men are experiencing eating, exercise, and body image (EEBI) disturbances. Clinician-researchers have identified a syndrome, termed muscle dysmorphia (MD), in which individuals, usually men, are pathologically preoccupied with their perceived lack of muscularity. The current study tested a modified version of an extant theoretical model of MD symptomatology as well as an alternative model of MD symptomatology. Over 700 adult men completed a demographic questionnaire, a symptom inventory, a self-esteem questionnaire, a measure of perfectionism, a measure of the media’s influence on EEBI disturbances, and measures of body dissatisfaction and MD symptoms. Structural equation modeling (SEM) was used to examine the goodness of fit of the proposed models. Overall, the first model demonstrated poor fit with the data. Conversely, the alternative model fit the data adequately. The alternative model was cross validated with a second sample, and also fit this data adequately.

Through the review of creativity research I have found that studies lack certain crucial parts: a) a theoretical framework for the study of creativity in science, b) studies considering the unique components related to scientific creativity, and c) studies of the interactions among key components through simultaneous analyses. The primary purpose of this study is to explore the dynamic interactions among four components (scientific proficiency, intrinsic motivation, creative competence, context supporting creativity) related to scientific creativity under the framework of scientific creativity. A total of 295 Korean middle school students participated. Well-known and commonly used measurements were selected and developed. Two scientific achievement scores and one score measured by performance-based assessment were used to measure student scientific knowledge/inquiry skills. Six items selected from the study of Lederman, Abd-El-Khalick, Bell, and Schwartz (2002) were used to assess how well students understand the nature of science. Five items were selected from the subscale of the scientific attitude inventory version II (Moore & Foy, 1997) to assess student attitude toward science. The Test of Creative Thinking-Drawing Production (Urban & Jellen, 1996) was used to measure creative competence. Eight items chosen from the 15 items of the Work Preference Inventory (1994) were applied to measure students' intrinsic motivation. To assess the level of context supporting creativity, eight items were adapted from measurement of the work environment (Amabile, Conti, Coon, Lazenby, and Herron, 1996). To assess scientific creativity, one open-ended science problem was used and three raters rated the level of scientific creativity through the Consensual Assessment Technique (Amabile, 1996). The results show that scientific proficiency and creative competence correlates with scientific creativity. Intrinsic motivation and context components do not predict scientific creativity. The strength of relationships between scientific proficiency and scientific creativity (estimate parameter=0.43) and creative competence and scientific creativity (estimate parameter=0.17) are similar [Δx²(.05)(1)=0.670, P > .05]. In specific analysis of structural model, I found that creative competence and scientific proficiency play a role of partial mediators among three components (general creativity, scientific proficiency, and scientific creativity). The moderate effects of intrinsic motivation and context component were investigated, but the moderation effects were not found.

The current generation of structural equation modeling (SEM) is loosely split in two divergent groups - covariance-based and variance-based structural equation modeling. The relative newness of variance-based SEM has limited the development of techniques that extend its applicability to non-metric data. This study focuses upon the extension of general linear model techniques within the variance-based platform of partial least squares structural equation modeling (PLS-SEM). This modeling procedure receives it name through the iterative PLS‑SEM algorithm's estimates of the coefficients for the partial ordinary least squares regression models in both the measurement model and the overall structural model. This research addresses the following research questions: (1) What are the appropriate measures for data segmentation within PLS‑SEM? (2) What are the appropriate steps for the analysis of rank-ordered path coefficients within PLS‑SEM? and (3) What is an appropriate model selection index for PLS‑SEM? The limited type of data to which PLS-SEM is applicable suggests an opportunity to extend the method for use with different data and as a result a broader number of applications. This study develops and tests several methodologies that are prevalent in the general linear model (GLM). The proposed data segmentation approaches posited and tested through post hoc analysis of structural model. Monte Carlo simulation allows demonstrating the improvement of the proposed model fit indices in comparison to the established indices found within the SEM literature. These posited PLS methods, that are logical transfers of GLM methods, are tested using examples. These tests enable demonstrating the methods and recommending reporting requirements.

Exclusive breastfeeding for the first six months of life has been shown to decrease morbidity and mortality of women and infants. Organizations such as the United Nations Children’s Fund (UNICEF, 2018), American Academy of Pediatrics (AAP, 2012), and the World Health Organization (WHO, 2017a) have universally endorsed exclusive breastfeeding for the first six months of life, and then continuation of breastfeeding for a minimum of one to two years, with only supplementation of other liquid or solid food sources. Breastfeeding rates in the United States have not met the minimum goals set forth by Healthy People 2020 (n.d.). Although 81% of U.S. mothers initiated breastfeeding after the birth of their infant, only 22% of mothers were found to be exclusively breastfeeding at six months postpartum (Centers for Disease Control and Prevention [CDC], 2016a). This prospective, longitudinal, structural equation modeling study examined millennial-aged, exclusively breastfeeding women within one month postpartum who were followers of at least one of 17 social media breastfeeding support groups. Relationships of the conceptual constructs within Pender’s (1996) revised health promotion model (RHPM); House’s (1981) dimensions of social support; and the added constructs of breastfeeding knowledge, breastfeeding confidence, and breastfeeding attitude were analyzed in an effort to better understand the variables that lead to sustained exclusive breastfeeding to six months. Data supported the use of the integrated model for breastfeeding women. The normed referenced chi-square (2) of 1.9 (CFI =.94, IFI =.94, NFI =.89, RMSEA =.06, CFI [PCFI] >.5) indicated a good model fit. Additionally, there were statistically significant gains in the confidence, knowledge, and attitude scores from pretest to follow-up at six months. Exclusive breastfeeding to six months was reported to be three times (66%) higher than the U.S. national average (22%) (CDC, 2016a). Future use of the integrated model has great potential to impact public health by the exploration of variables that promote exclusive breastfeeding to six months. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2018. / FAU Electronic Theses and Dissertations Collection

Selecting an appropriate model is a crucial issue for applying structural equation models (SEMs) in real applications. Due to the model complexity, however, it is quite challenging to perform model selection on semiparametric SEMs with functional structural equations. In this thesis, we propose a modified Bayesian adaptive group Lasso procedure to perform model selection and estimation for semiparametric SEMs. By considering a novel formulation of basis expansions to approximate the unknown functions with certain penalties imposed, we are able to introduce a partial linear structure that combines the advantages of linear and nonparametric formulations for structural equations. The nonlinear, linear, or none structures in structural equations can be automatically detected with the proposed method. In addition, the group Lasso with adaptive penalties not only largely alleviates the model selection difficulties caused by the group effects and correlations introduced by basis expansions of latent variables, but also reduces the bias of traditional Lasso procedures. Simulation studies demonstrate that the proposed methodology performs satisfactorily. The proposed method is applied to analyze a real data set of diabetic kidney disease, which provides us some meaningful insights. / 在结构方程模型的实际应用中，选择一个合适的模型是一个核心问题。但是由于模型的复杂性，对于含有函数型结构的半参数结构方程模型进行模型选择十分困难。在本文中，我们提出了一种新的贝叶斯自适应群Lasso，并应用它来对半参数结构方程模型同时进行参数估计和模型选择。我们在非参数结构方程模型中引入了部分线性结构，并通过一种新的基底函数展开来近似结构方程里的未知函数。这种结构同时具备了线性模型和非参数模型的优势。本文的方法可以自动识别半参数结构方程模型里面的非线性和线性结构，并筛除不重要的变量。这种带有自适应惩罚的群Lasso不仅减小了传统Lasso方法在估计参数时产生的偏差，而且解决了由潜变量的基底表示导致的组效应和相关性引起的模型选择的困难。由模拟实验的结果可以看出本文提出的方法十分有效。我们还应用所提出的方法分析了一组关于糖尿病型肾病的数据，并得到了一些有意义的结果。 / Feng, Xiangnan. / Thesis M.Phil. Chinese University of Hong Kong 2014. / Includes bibliographical references (leaves 51-56). / Abstracts also in Chinese. / Title from PDF title page (viewed on 18, October, 2016). / Detailed summary in vernacular field only.

Structural equation models (SEMs) are commonly used in behavioral, educational, medical, and social sciences. Lots of software, such as EQS, LISREL, MPlus, and WinBUGS, can be used for the analysis of SEMs. Also many methods have been developed to analyze SEMs. One popular method is the Bayesian approach. An important issue in the Bayesian analysis of SEMs is model selection. In the literature, Bayes factor and deviance information criterion (DIC) are commonly used statistics for Bayesian model selection. However, as commented in Chen et al. (2004), Bayes factor relies on posterior model probabilities, in which proper prior distributions are needed. And specifying prior distributions for all models under consideration is usually a challenging task, in particular when the model space is large. In addition, it is well known that Bayes factor and posterior model probability are generally sensitive to the choice of the prior distributions of the parameters. Furthermore the computational burden of Bayes factor is heavy. Alternatively, criterion-based methods are attractive in the sense that they do not require proper prior distributions in general, and the computation is quite simple. One of commonly used criterion-based methods is DIC, which however assumes the posterior mean to be a good estimator. For some models like the mixture SEMs, WinBUGS does not provide the DIC values. Moreover, if the difference in DIC values is small, only reporting the model with the smallest DIC value may be misleading. In this thesis, motivated by the above limitations of the Bayes factor and DIC, a Bayesian model selection criterion called the Lv measure is considered. It is a combination of the posterior predictive variance and bias, and can be viewed as a Bayesian goodness-of-fit statistic. The calibration distribution of the Lv measure, defined as the prior predictive distribution of the difference between the Lv measures of the candidate model and the criterion minimizing model, is discussed to help understanding the Lv measure in detail. The computation of the Lv measure is quite simple, and the performance is satisfactory. Thus, it is an attractive model selection statistic. In this thesis, the application of the Lv measure to various kinds of SEMs will be studied, and some illustrative examples will be conducted to evaluate the performance of the Lv measure for model selection of SEMs. To compare different model selection methods, Bayes factor and DIC will also be computed. Moreover, different prior inputs and sample sizes are considered to check the impact of the prior information and sample size on the performance of the Lv measure. In this thesis, when the performances of two models are similar, the simpler one is selected. / Li, Yunxian. / Adviser: Song Xinyuan. / Source: Dissertation Abstracts International, Volume: 72-04, Section: B, page: . / Thesis (Ph.D.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (leaves 116-122). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.

A real empirical study was conducted to illustrate the application of the unconstrained approach. The genuine study focused on the interaction effect of music self-concept and music-domain importance on the global self-concept. The result showed that structural equation analysis was advantageous over the traditional regression analysis, while such superiority of the structural equation modeling approach was more prominent in higher-order structural equation models. As expected, the estimated main and interaction effects in the quasi-standardized solution obtained using the centered data coincided with those using the standardized data in different order structural models. / Concepts and issues related to standardized solutions for the latent interaction model were discussed. Quasi-standardized solution was proposed and formulated by using the estimates of the original solution and the ordinary standardized solution. Some properties of the quasi-standardized solution were mathematically derived and proved, which included the demonstration that the main and interaction effects were scale free, so were the loading and the Chi-square of model fit, while t statistics of main and interaction effects were approximate scale free. / Six simulation studies, four for the latent interaction models, and two for the latent quadratic models were conducted to compare the performances of the four approaches. Results generally showed that the QML approach and the constrained approach behaved similarly, while the performance of the unconstrained approach was close to that of the GAPI approach. Under the normal distribution condition, the QML approach performed the best among the four approaches in terms of lack of bias, precision, and power. However, with moderate and large sample sizes (N=200 or above), the differences among the four approaches were systematically smaller, with similar bias and precision. Under nonnormal conditions, the unconstrained approach was more robust, with a smaller bias and predictable type I error rate (near the significant level), and its precision and power increased as the sample size increased. These results supported the use of the unconstrained approach for the analyses of latent interaction and quadratic models. / The unconstrained approach was extended to estimate interaction effects in latent growth models. With the indicators of the interaction term formed by the products of differences (rather than using the usual indicator product strategy), a simplified full interaction model for the latent growth model was proposed. The model was further simplified when only the interaction between change rates was considered. Importantly, the unconstrained approach was an appropriate method for analyses of such simplified full interaction model for latent growth model, which also constituted a unique contribution of this dissertation. / Through a series of related studies, the research attempted to identify better estimation approaches and modeling techniques for latent interaction and quadratic effects. The literature review provided a conceptual framework for the unconstrained approach which was recommended for its simplicity and robustness. Three other approaches, namely, the constrained, the partially constrained (i.e., the generalized appended product indicator, GAPI), and the quasi-maximum likelihood (QML) approaches were selected and compared with the unconstrained approach. / 溫忠粦. / 論文(哲學博士)--香港中文大學, 2005. / 參考文獻(p. 191-203). / Adviser: Kit-Tai Hau. / Source: Dissertation Abstracts International, Volume: 67-01, Section: A, page: 0160. / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts also in English. / School code: 1307. / Lun wen (Zhe xue bo shi)--Xianggang Zhong wen da xue, 2005. / Can kao wen xian (p. 191-203). / Wen Zhonglin.

Keywords: Bayesian analysis, Finite mixture, Gibbs sampler, Langevin-Hasting sampler, MH sampler, Model comparison, Nonrecursive nonlinear structural equation model, Path sampling. / Structural equation models (SEMs) have been applied extensively to management, marketing, behavioral, and social sciences, etc for studying relationships among manifest and latent variables. Motivated by more complex data structures appeared in various fields, more complicated models have been recently developed. For the developments of SEMs, there is a usual assumption about the regression coefficient of the underlying latent variables. On themselves, more specifically, it is generally assumed that the structural equation modeling is recursive. However, in practice, nonrecursive SEMs are not uncommon. Thus, this fundamental assumption is not always appropriate. / The main objective of this thesis is to relax this assumption by developing some efficient procedures for some complex nonrecursive nonlinear SEMs (NNSEMs). The work in the thesis is based on Bayesian statistical analysis for NNSEMs. The first chapter introduces some background knowledge about NNSEMs. In chapter 2, Bayesian estimates of NNSEMs are given, then some statistical analysis topics such as standard error, model comparison, etc are discussed. In chapter 3, we develop an efficient hybrid MCMC algorithm to obtain Bayesian estimates for NNSEMs with mixed continuous and ordered categorical data. Also, some statistical analysis topics are discussed. In chapter 4, finite mixture NNSEMs are analyzed with the Bayesian approach. The newly developed methodologies are all illustrated with simulation studies and real examples. At last, some conclusion and discussions are included in Chapter 5. / Li, Yong. / "July 2007." / Adviser: Sik-yum Lee. / Source: Dissertation Abstracts International, Volume: 69-01, Section: B, page: 0398. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (p. 99-111). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese. / School code: 1307.

Submitted by Inácio de Oliveira Lima Neto (inacio.neto@inpa.gov.br) on 2018-10-01T14:38:01Z No. of bitstreams: 2 João_Gabriel_Rafaelli.pdf: 2157835 bytes, checksum: 8d523aee7395e3c81de2736e95f7010b (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2018-10-01T14:38:02Z (GMT). No. of bitstreams: 2 João_Gabriel_Rafaelli.pdf: 2157835 bytes, checksum: 8d523aee7395e3c81de2736e95f7010b (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2018-03-02 / Fundação de Amparo à Pesquisa do Estado do Amazonas - FAPEAM / Agroforestry system is a land use technique practiced a long time around the world. Currently, an attention has been paid to this practice, with several projects and organizations working with the optimization of this technique. Among many ways of establishing an agroforestry system, taking into account the species to be used, the environmental conditions and the type of system to be implemented; the understanding of the specific factors that can influence the plantations are of utmost importance for its success. The present work aimed to evaluate the initial development of seedlings from 16 species planted in different lands, influenced by environmental factors and management of local farmers. The study was carried out at the Andirá-Marau Indigenous Reserve (Amazonas - Brazil) in eight different plantations with different agricultural practices. The parameters of plant performance analyzed were: Carbon Stock (CARBON), Absolute Diameter Increment (ADI), Relative Growth Rate (RGR) and Specific Leaf Area (SLA). As factors influencing the performance of seedlings were analyzed: Soil Quality (chemical and physical), percentage of Vegetation Cover (VC), Forest Distance (FD), Above Ground Biomass (AGB), Species Richness (SP_RICH), Litter Biomass, Charcoal Biomass, Nearest Next Neighbor and Competition Index. As a descriptive analysis, the soils were analyzed using ANOVA (two-factor) testing soil depths and areas. Also, the plantations were analyzed in terms of: area size, seedling survival, species composition, spacing, height and biomass. As an exploratory data analysis we used linear regressions between each performance trait and each influence factor. Later, we used the Structural Equation Modeling analysis to test how the factors together influence the performance of the seedlings. Finally, to test how the general models for all species influence in a specie-specific way, we tested models for Carapa guianensis Aubl. As results, it can be observed that during the project 45% of the seedlings died (9% between Dec 2014 and Dec 2015, 32% between Dec 2015 and Aug 2016, 11% between Aug 2016 and Feb 2017), mainly due to large dry season on the 2nd semester. Ingá, Urucum, Andiroba and Graviola species showed great variability in biomass accumulation, while Acerola, Cumaru, Guaraná and Mahogany varied much less. The exploratory analysis showed that RGR was positively influenced by FD and soil nutrients Mn, Ca, Mg, K and CPB and negatively by Fe; the Carbon Stock was positively influenced by FD, Coal Biomass, Nearby Neighbor, by soil nutrients Al, Mg, K, C, N, CEC and negatively by soil Density and Fe; ADI was positively influenced by FD, Neighbor Next, by nutrients Al, Mg, K, C, N, CEC and negatively by soil Density and Fe; SLA was positively influenced by VC and AGB. In the general models for all species, in SEM, we could observe that Carbon Stock had a 14% variation explained by the model, ADI had 14%, RGR had 11% and SLA had 10%. For the specific model (Carapa guianensis) the percentage of variation explained by the models was: Carbon Stock with 31%, ADI with 27%, RGR with 10% and SLA with 71%. We can conclude that soil factors (C, N, P, Mg, CEC, pH, Texture and Density), Biomass of Serrapilheira, VC and Next Neighbor, had greater influence on the initial performance of the seedlings planted in different agroforestry systems, which have to be taken into account for management practices. / Sistemas agroflorestais são formas de uso da terra utilizadas por muito tempo ao redor do mundo. Atualmente tem-se prestado maior atenção a essa prática, com diversos projetos e organizações trabalhando com a otimização das técnicas, para um melhor desenvolvimento desses sistemas. Dentre as diversas maneiras de se estabelecer um sistema agroflorestal, levando em consideração as espécies a serem utilizadas, o ambiente em que se encontra e o tipo de sistema a ser implementado, o entendimento dos fatores que possam influenciar os plantios são de suma importância para um maior sucesso desses. O presente trabalho teve como objetivo avaliar o desenvolvimento inicial de mudas de 16 espécies plantadas em diferentes ambientes, pela influência de fatores ambientais e do manejo de agricultores locais. O estudo foi realizado na Terra Indígena Andirá-Marau (Amazonas - Brasil) e contou com oito diferentes plantios em ambientes com diferentes práticas agrícolas. Foram avaliados os parâmetros de desempenho vegetal o Estoque de Carbono (CARBON), o Incremento Absoluto do Diâmetro (ADI), a Taxa de Crescimento Relativo (RGR) e a Área Foliar Específica (SLA). Como fatores de influência no desempenho das mudas foram avaliados: a Qualidade dos Solos (química e física), a porcentagem de Cobertura Vegetal (VC), a Distância dos plantios para a Floresta (FD), Biomassa Acima do Solo (AGB), Riqueza de Espécies (SP_RICH), Biomassa da Serrapilheira, Biomassa de Carvão, Vizinho Próximo das mudas plantadas e Índice de Competição. Como análise descritiva, os solos foram analisados utilizando o teste ANOVA (two-factor) entre as profundidades e a áreas. Também de forma descritiva foram analisados os plantios quanto: sobrevivência das mudas, composição de espécies, espaçamento, altura e biomassa. Para análise dos dados foram utilizadas regressões lineares entre cada medida de desempenho e cada fator de influência, como forma exploratória dos dados. Posteriormente utilizo-se a análise Structural Equation Modeling (SEM) para testar como os fatores influenciam o desempenho das mudas de forma conjunta. Por fim, para testar como os modelos gerais para todas as espécies influenciam de maneira específica, foi testado modelos para a espécie Carapa guianensis Aubl. Como resultado, pode-se observar que ao longo do projeto 45% das mudas morreram (9% entre Dez 2014 e Dez 2015, 32% entre Dez 2015 e Ago 2016, 11% entre Ago 2016 e Fev 2017), devido principalmente a grande seca no 2o. semestre de 2015. As espécies Ingá, Urucum, Andiroba e Graviola mostraram grande variabilidade no acumulo de biomassa, enquanto Acerola, Cumaru, Guaraná e Mogno variaram muito menos. Já a análise exploratória nos mostrou que o RGR foi influenciado positivamente por FD e pelos nutrientes do solo Mn, Ca, Mg, K e CEC e negativamente por Fe; o Estoque de Carbono foi influenciado positivamente por FD, Biomassa de Carvão, Vizinho Próximo, pelos nutrientes do solo Al, Mg, K, C, N, CEC e negativamente por Densidade do Solo e Fe; o ADI foi influenciado positivamente por FD, Vizinho Próximo, pelos nutrientes Al, Mg, K, C, N, CEC e negativamente por Densidade do Solo e Fe; SLA foi influenciada positivamente por VC e AGB. Nos modelos gerais para todas as espécies, em SEM, vimos que o Estoque de Carbono teve 14% de variação explicada pelo modelo, ADI teve 14%, RGR teve 11% e SLA teve 10%. Para o modelo específico (Carapa guianensis) a porcentagem de variação explicada pelos modelos foram, Estoque de Carbono com 31%, ADI com 27 %, RGR com 10% e SLA com 71%. Podemos concluir que os fatores do solo (C, N, P, Mg, CEC, pH, Textura e Densidade), Biomassa da Serrapilheira, VC e Vizinho Próximo, tiveram maior influência no desempenho inicial das mudas nos sistemas agroflorestais implantados, devendo ser levadas em consideração nas práticas de manejo.