Validation of the Item-Attribute Matrix in TIMSS-Mathematics Using Multiple Regression and the LSDM

The purposes of this study were (1) to validate of the item-attribute matrix using two levels of attributes (Level 1 attributes and Level 2 sub-attributes), and (2) through retrofitting the diagnostic models to the mathematics test of the Trends in International Mathematics and Science Study (TIMSS), to evaluate the construct validity of TIMSS mathematics assessment by comparing the results of two assessment booklets. Item data were extracted from Booklets 2 and 3 for the 8th grade in TIMSS 2007, which included a total of 49 mathematics items and every student's response to every item. The study developed three categories of attributes at two levels: content, cognitive process (TIMSS or new), and comprehensive cognitive process (or IT) based on the TIMSS assessment framework, cognitive procedures, and item type. At level one, there were 4 content attributes (number, algebra, geometry, and data and chance), 3 TIMSS process attributes (knowing, applying, and reasoning), and 4 new process attributes (identifying, computing, judging, and reasoning). At level two, the level 1 attributes were further divided into 32 sub-attributes. There was only one level of IT attributes (multiple steps/responses, complexity, and constructed-response). Twelve Q-matrices (4 originally specified, 4 random, and 4 revised) were investigated with eleven Q-matrix models (QM1 ~ QM11) using multiple regression and the least squares distance method (LSDM). Comprehensive analyses indicated that the proposed Q-matrices explained most of the variance in item difficulty (i.e., 64% to 81%). The cognitive process attributes contributed to the item difficulties more than the content attributes, and the IT attributes contributed much more than both the content and process attributes. The new retrofitted process attributes explained the items better than the TIMSS process attributes. Results generated from the level 1 attributes and the level 2 attributes were consistent. Most attributes could be used to recover students' performance, but some attributes' probabilities showed unreasonable patterns. The analysis approaches could not demonstrate if the same construct validity was supported across booklets. The proposed attributes and Q-matrices explained the items of Booklet 2 better than the items of Booklet 3. The specified Q-matrices explained the items better than the random Q-matrices.

Deriva genética de caracteres quantitativos em milho

A obtenção de genótipos superiores no melhoramento de plantas depende da existência de variabilidade genética. A existência de coleções de germoplasma representativas e a utilização de um tamanho adequado de amostra são fundamentais para a preservação das frequências alélicas e genotípicas, diminuindo a perda de variabilidade genética e postergando o aparecimento dos efeitos da deriva genética. Assim, teve-se como objetivo avaliar os efeitos da deriva genética em caracteres quantitativos em subpopulações de milho. Este estudo foi realizado a partir das populações originais BR-105 e BR-106, das quais 10 subpopulações foram obtidas em cada um dos cinco ciclos sucessivos de amostragem com tamanho efetivo reduzido, totalizando 50 subpopulações para cada população original, as quais foram posteriormente autofecundadas, gerando um nível a mais de endogamia. Os tratamentos foram constituídos de 10 amostras da população original sem autofecundação, 10 amostras com autofecundação, 50 subpopulações obtidas da população original e 50 subpopulações autofecundadas, totalizando 120 tratamentos para cada população, avaliados separadamente. Utilizou-se o delineamento em blocos casualizados no esquema de parcelas subdivididas em faixas hierárquico, em quatro ambientes com duas repetições por ambiente. Os caracteres avaliados foram produção de grãos (PG), prolificidade (PROL), comprimento e diâmetro de espigas (CE e DE), número de fileiras por espiga (NFE), número de grãos por fileira (NGF), altura de planta e espiga (AP e AE), florescimento masculino e feminino (FM e FF) e número de ramificações do pendão (NRP). Foram estimados os efeitos da deriva genética entre as médias das subpopulações nos dois níveis de endogamia e os efeitos da depressão por endogamia nas subpopulações dentro dos ciclos. Posteriormente, realizaram-se análises de regressão linear para as subpopulações nos dois níveis de endogamia, separadamente, e em conjunto. Foi verificada uma grande variação nas médias das subpopulações ao longo dos ciclos, indicando que a deriva genética causou diferenciação entre as mesmas e que estas se diferenciaram das populações originais. Detectaram-se efeitos significativos da deriva genética nas populações não autofecundadas para todos os caracteres avaliados, em maior número para PG, já que este caráter é mais sensível à deriva genética por possuir maior grau de dominância que os demais. Houve diminuição no número de estimativas de deriva significativas para as populações autofecundadas, incluindo mudanças na magnitude e no sinal das mesmas em relação às populações não autofecundadas. Para as estimativas de depressão por endogamia, os caracteres PG, NGF, FM e FF apresentaram maior quantidade de estimativas significativas que os demais. Para a maioria dos caracteres, a regressão linear explicou a maior parte da variação encontrada com o aumento dos coeficientes de endogamia. As populações BR-105 e BR-106, por terem estruturas genéticas distintas, apresentaram performances diferentes quanto aos efeitos da deriva genética. Enfim, como a deriva genética interfere na integridade genética das populações, torna-se importante considerar seus efeitos na coleta e manutenção dos bancos de germoplasma e nas populações utilizadas no melhoramento genético de plantas.

Análise da aderência de práticas ágeis na cultura de startups de software: o mapeamento de práticas através do SEMAT Kernel.

Este trabalho analisa os principais métodos ágeis utilizados em empresas startup, como scrum, extreme programming, kanban e lean, isolando suas práticas e mapeando-as no Kernel do SEMAT para escolher os elementos essenciais da engenharia de software que estão relacionados a cada prática de forma independente. Foram identificadas 34 práticas que foram reduzidas a um conjunto de 26 pelas similaridades. Um questionário foi desenvolvido e aplicado no ambiente de startups de software para a avaliação do grau de utilização de cada determinada prática. Através das respostas obtidas foi possível a identificação de um subconjunto de práticas com utilização acima de 60% onde todos os elementos essenciais da engenharia de software são atendidos, formando um conjunto mínimo de práticas capazes de sustentar este tipo específico de ambiente.

GE models and algorithms for condensed phase equilibrium data regression in ternary systems: limitations and proposals

Phase equilibrium data regression is an unavoidable task necessary to obtain the appropriate values for any model to be used in separation equipment design for chemical process simulation and optimization. The accuracy of this process depends on different factors such as the experimental data quality, the selected model and the calculation algorithm. The present paper summarizes the results and conclusions achieved in our research on the capabilities and limitations of the existing GE models and about strategies that can be included in the correlation algorithms to improve the convergence and avoid inconsistencies. The NRTL model has been selected as a representative local composition model. New capabilities of this model, but also several relevant limitations, have been identified and some examples of the application of a modified NRTL equation have been discussed. Furthermore, a regression algorithm has been developed that allows for the advisable simultaneous regression of all the condensed phase equilibrium regions that are present in ternary systems at constant T and P. It includes specific strategies designed to avoid some of the pitfalls frequently found in commercial regression tools for phase equilibrium calculations. Most of the proposed strategies are based on the geometrical interpretation of the lowest common tangent plane equilibrium criterion, which allows an unambiguous comprehension of the behavior of the mixtures. The paper aims to show all the work as a whole in order to reveal the necessary efforts that must be devoted to overcome the difficulties that still exist in the phase equilibrium data regression problem.

An integral security kernel

As the user base of the Internet has grown tremendously, the need for secure services has increased accordingly. Most secure protocols, in digital business and other fields, use a combination of symmetric and asymmetric cryptography, random generators and hash functions in order to achieve confidentiality, integrity, and authentication. Our proposal is an integral security kernel based on a powerful mathematical scheme from which all of these cryptographic facilities can be derived. The kernel requires very little resources and has the flexibility of being able to trade off speed, memory or security; therefore, it can be efficiently implemented in a wide spectrum of platforms and applications, either software, hardware or low cost devices. Additionally, the primitives are comparable in security and speed to well known standards.

Economic crises and tourism competitiveness: A Markov swtiching regression approach

Authors discuss the effects that economic crises generate on the global market shares of tourism destinations, through a series of potential transmission mechanisms based on the main economic competitiveness determinants identified in the previous literature using a non-linear approach. Specifically a Markov Switching Regression approach is used to estimate the effect of two basic transmission mechanisms: reductions of internal and external tourism demands and falling investment.

Exports and Capacity Constraints: A smooth transition regression model for six euro-area countries. CEPS Working Document No. 395/May 2014

The significant gains in export market shares made in a number of vulnerable euro-area crisis countries have not been accompanied by an appropriate improvement in price competitiveness. This paper argues that, under certain conditions, firms consider export activity as a substitute for serving domestic demand. The strength of the link between domestic demand and exports is dependent on capacity constraints. Our econometric model for six euro-area countries suggests domestic demand pressure and capacity-constraint restrictions as additional variables of a properly specified export equation. As an innovation to the literature, we assess the empirical significance through the logistic and the exponential variant of the non-linear smooth transition regression model. We find that domestic demand developments are relevant for the short-run dynamics of exports in particular during more extreme stages of the business cycle. A strong substitutive relationship between domestic and foreign sales can most clearly be found for Spain, Portugal and Italy, providing evidence of the importance of sunk costs and hysteresis in international trade.

LOGITCPRPLOT: Stata module to graph component-plus-residual plot for logistic regression

logitcprplot can be used after logistic regression for graphing a component-plus-residual plot (a.k.a. partial residual plot) for a given predictor, including a lowess, local polynomial, restricted cubic spline, fractional polynomial, penalized spline, regression spline, running line, or adaptive variable span running line smooth

KDENS: Stata module for univariate kernel density estimation

kdens produces univariate kernel density estimates and graphs the result. kdens supplements official Stata's kdensity. Important additions are: adaptive (i.e. variable bandwidth) kernel density estimation, several automatic bandwidth selectors including the Sheather-Jones plug-in estimator, pointwise variability bands and confidence intervals, boundary correction for variables with bounded domain, fast binned approximation estimation. Note that the moremata package, also available from SSC, is required.

RRLOGIT: Stata module to estimate logistic regression for randomized response data

rrlogit fits a maximum-likelihood logistic regression for randomized response data.

WGTTEST: Stata module to test the impact of sampling weights in regression analysis

wgttest performs a test proposed by DuMouchel and Duncan (1983) to evaluate whether the weighted and unweighted estimates of a regression model are significantly different.

Statistical analysis of the goodness of classical factor analysis regression (CFAR) /

Cover title.

OPTREG - an interactive computer program for optimization and regression. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

An analysis of the regression model for nonsaturating logic circuit analysis.

Also issued as thesis (M.S.) University of Illinois.

A virtual address kernel modification for UNIX /

"February 1980."