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Interpreting and Visualizing Regression Models Using Stata, Second Edition provides clear and simple examples illustrating how to interpret and visualize a wide variety of regression models. Including over 200 figures, the book illustrates linear models with continuous predictors (modeled linearly, using polynomials, and piecewise), interactions of continuous predictors, categorical predictors, interactions of categorical predictors, and interactions of continuous and categorical predictors. The book also illustrates how to interpret and visualize results from multilevel models, models where time is a continuous predictor, models with time as a categorical predictor, nonlinear models (such as logistic or ordinal logistic regression), and models involving complex survey data. The examples illustrate the use of the margins, marginsplot, contrast, and pwcompare commands. This new edition reflects new and enhanced features added to Stata, most importantly the ability to label statistical output using value labels associated with factor variables. As a result, output regarding marital status is labeled using intuitive labels like Married and Unmarried instead of using numeric values such as 1 and 2. All the statistical output in this new edition capitalizes on this new feature, emphasizing the interpretation of results based on variables labeled using intuitive value labels. Additionally, this second edition illustrates other new features, such as using transparency in graphics to more clearly visualize overlapping confidence intervals and using small sample-size estimation with mixed models. If you ever find yourself wishing for simple and straightforward advice about how to interpret and visualize regression models using Stata, this book is for you.

#SBIB:303H4 --- #SBIB:303H520 --- Regression analysis --- Analysis, Regression --- Linear regression --- Regression modeling --- Multivariate analysis --- Structural equation modeling --- Informatica in de sociale wetenschappen --- Methoden sociale wetenschappen: techniek van de analyse, algemeen --- Computer simulation --- Stata.

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This book provides a concise point of reference for the most commonly used regression methods. It begins with linear and nonlinear regression for normally distributed data, logistic regression for binomially distributed data, and Poisson regression and negative-binomial regression for count data. It then progresses to these regression models that work with longitudinal and multi-level data structures. The volume is designed to guide the transition from classical to more advanced regression modeling, as well as to contribute to the rapid development of statistics and data science. With data and computing programs available to facilitate readers' learning experience, Statistical Regression Modeling promotes the applications of R in linear, nonlinear, longitudinal and multi-level regression. All included datasets, as well as the associated R program in packages nlme and lme4 for multi-level regression, are detailed in Appendix A. This book will be valuable in graduate courses on applied regression, as well as for practitioners and researchers in the fields of data science, statistical analytics, public health, and related fields.

Regression analysis. --- R (Computer program language) --- GNU-S (Computer program language) --- Domain-specific programming languages --- Analysis, Regression --- Linear regression --- Regression modeling --- Multivariate analysis --- Structural equation modeling --- Anàlisi de regressió --- R (Llenguatge de programació) --- GNU-S (Llenguatge de programació) --- Llenguatges de programació --- Model de regressió --- Regressió lineal --- Estadística --- Estadística matemàtica --- Correlació múltiple (Estadística) --- Correlació (Estadística) --- Models d'equacions estructurals --- Statistics. --- Programming languages (Electronic computers). --- Statistical Theory and Methods. --- Applied Statistics. --- Programming Language. --- Computer languages --- Computer program languages --- Computer programming languages --- Machine language --- Electronic data processing --- Languages, Artificial --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics

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The International Symposium on Future ICT (Future-ICT 2019) in conjunction with the 4th International Symposium on Mobile Internet Security (MobiSec 2019) was held on 17–19 October 2019 in Taichung, Taiwan. The symposium provided academic and industry professionals an opportunity to discuss the latest issues and progress in advancing smart applications based on future ICT and its relative security. The symposium aimed to publish high-quality papers strictly related to the various theories and practical applications concerning advanced smart applications, future ICT, and related communications and networks. It was expected that the symposium and its publications would be a trigger for further related research and technology improvements in this field.

Technology: general issues --- normalized cross-correlation --- fast algorithm --- first-order moment --- systolic array --- multiplication complexity --- IoT --- sustainability --- hybrid RAM disk --- direct byte read --- secondary storage --- operating system --- PM2.5 concentration estimation --- digital image processing --- automatic region of interest selection --- data exclusion --- linear regression --- census transform --- sparse census transform --- disparity --- stereo vision --- data hiding --- multidimensional --- embedding efficiency --- mini-SuDoKu --- security --- NAND flash memory --- P/E cycle --- compression --- adaptive ECC --- RAID scattering --- stripe log --- parity --- secret image sharing --- maze matrix --- cheat detection --- cheater identification --- controller area network --- intrusion detection system --- in-vehicle network security --- machine learning --- hierarchical approach --- anomaly detection --- MLHC --- IWSNs --- error models --- IEEE 802.15.4 --- second-order Markov chain --- OpenWSN --- transmission reliability --- certificateless signature --- aggregate signature --- arbitrated signature --- public key replace attack --- epidemic management --- GNSS/GPS --- infectious disease --- isolation --- social networking service --- hot spot --- adaptive data rate (ADR) --- transmit power control (TPC) --- time division multiple access (TDMA) --- wireless sensor network (WSN) --- power consumption --- Internet of Things (IoT) --- n/a

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Amidst impending climate change and enhanced pollution levels around the globe, the need of the hour is to develop bio-based materials that are sustainable and possess comparable performance properties to their synthetic counterparts. In light of the aforementioned, numerous investigations are being conducted to identify, process, and create materials that are concurrently innocuous towards the environment and have superior properties. This book is a collection of such scientific articles that propagate novel ideas for the development of polymeric composite materials, which have application potential in numerous fields such as medicine, automobile, aviation, construction, etc. It also contains a pedagogical article that proposes some strategies to continue experimental research during pandemics. This book will provide readers a quick glance into recent developments regarding polymeric materials and will encourage them to propagate these research ideas further.

History of engineering & technology --- solid urban waste --- formaldehyde --- durability --- electrical properties --- mechanical properties --- recycling --- epoxy resin --- flammability --- heat release rate --- microscale combustion calorimetry --- multiple linear regression --- adaptive neuro-fuzzy inference system --- polyvinyl alcohol (PVA) --- bionanocomposites --- nanomechanical behaviour --- thin films --- particle size --- model free --- model fitting --- avrami–eroféev --- DAEM --- superhydrophobic surfaces --- self-healing --- natural hierarchical microstructures --- wood --- bio-composite --- linear low density polyethylene --- performance --- straws --- biocomposites --- nanofibers --- electrospinning --- cell culture --- graphene oxide --- barrier properties --- poly(lactic acid) --- clay --- nanocomposite --- permeability --- bacterial cellulose --- metal organic framework --- adsorption --- chitosan --- composite nanofibers --- silk fibroin --- polycaprolactone --- Taguchi --- rheological properties --- DMA --- injection molding --- thermal properties --- natural fibers --- biochar --- carbon fillers --- nanocomposites --- flame retardants --- fire --- n/a --- PHB --- natural fiber --- compatibilizer --- cellulose --- biocomposite --- avrami-eroféev

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The dynamics of systems have proven to be very powerful tools in understanding the behavior of different natural phenomena throughout the last two centuries. However, the attributes of natural systems are observed to deviate from their classical states due to the effect of different types of uncertainties. Actually, randomness and impreciseness are the two major sources of uncertainties in natural systems. Randomness is modeled by different stochastic processes and impreciseness could be modeled by fuzzy sets, rough sets, Dempster–Shafer theory, etc.

Research & information: general --- Mathematics & science --- Fuzzy MARCOS --- Fuzzy PIPRECIA --- traffic risk --- TFN --- MCDM --- dual-rotor --- multi-frequency excitation --- non-intrusive calculation --- metamodel --- NDSL model --- AHP --- criteria weights --- pairwise comparisons --- AES --- PC --- MIMO discrete-time system --- state feedback and output feedback --- parameter dependence --- D numbers --- fuzzy sets --- DEMATEL --- multi-criteria decision-making --- multi-criteria optimization --- RAFSI method --- performance comparison --- rank reversal --- Magnetic Resonance Imaging (MRI) --- wavelet transform --- GARCH --- LLA --- LDA --- KNN --- BWM --- BWM-I --- multi-criteria --- renewable energy --- the CCSD method --- the ITARA method --- the MARCOS method --- stackers --- logistics --- ensemble techniques --- data mining --- classification and discrimination --- linear regression --- applied mathematics general --- prediction theory --- theory of mathematical modeling --- medical applications --- empathic building --- fuzzy grey cognitive maps --- Thayer’s emotion model --- artificial emotions --- affective computing --- n/a --- Thayer's emotion model