Linear Regression Models for Panel Data Using SAS, Stata, LIMDEP, and SPSS

Panel (or longitudinal) data are cross-sectional and time-series. There are multiple entities, each of which has repeated measurements at different time periods. U.S. Census Bureau’s Census 2000 data at the state or county level are cross-sectional but not time-series, while annual sales figures of Apple Computer Inc. for the past 20 years are time series but not cross-sectional. If annual sales data of IBM, LG, Siemens, Microsoft, and AT&T during the same periods are also available, they are panel data. The cumulative General Social Survey (GSS), American National Election Studies (ANES), and Current Population Survey (CPS) data are not panel data in the sense that individual respondents vary across survey years. Panel data may have group effects, time effects, or the both, which are analyzed by fixed effect and random effect models

Regression Models for Ordinal and Nominal Dependent Variables Using SAS, Stata, LIMDEP, and SPSS

A categorical variable here refers to a variable that is binary, ordinal, or nominal. Event count data are discrete (categorical) but often treated as continuous variables. When a dependent variable is categorical, the ordinary least squares (OLS) method can no longer produce the best linear unbiased estimator (BLUE); that is, OLS is biased and inefficient. Consequently, researchers have developed various regression models for categorical dependent variables. The nonlinearity of categorical dependent variable models makes it difficult to fit the models and interpret their results

Univariate Analysis and Normality Test Using SAS, Stata, and SPSS

Descriptive statistics provide important information about variables to be analyzed. Mean, median, and mode measure central tendency of a variable. Measures of dispersion include variance, standard deviation, range, and interquantile range (IQR). Researchers may draw a histogram, stem-and-leaf plot, or box plot to see how a variable is distributed. Statistical methods are based on various underlying assumptions. One common assumption is that a random variable is normally distributed. In many statistical analyses, normality is often conveniently assumed without any empirical evidence or test. But normality is critical in many statistical methods. When this assumption is violated, interpretation and inference may not be reliable or valid. The t-test and ANOVA (Analysis of Variance) compare group means, assuming a variable of interest follows a normal probability distribution. Otherwise, these methods do not make much sense. Figure 1 illustrates the standard normal probability distribution and a bimodal distribution. How can you compare means of these two random variables? There are two ways of testing normality (Table 1). Graphical methods visualize the distributions of random variables or differences between an empirical distribution and a theoretical distribution (e.g., the standard normal distribution). Numerical methods present summary statistics such as skewness and kurtosis, or conduct statistical tests of normality. Graphical methods are intuitive and easy to interpret, while numerical methods provide objective ways of examining normality

Regression Models for Binary Dependent Variables Using Stata, SAS, R, LIMDEP, and SPSS

A categorical variable here refers to a variable that is binary, ordinal, or nominal. Event count data are discrete (categorical) but often treated as continuous variables. When a dependent variable is categorical, the ordinary least squares (OLS) method can no longer produce the best linear unbiased estimator (BLUE); that is, OLS is biased and inefficient. Consequently, researchers have developed various regression models for categorical dependent variables. The nonlinearity of categorical dependent variable models makes it difficult to fit the models and interpret their results

Confirmatory Factor Analysis using Amos, LISREL, Mplus, SAS/STAT CALIS

Factor analysis is a statistical method used to find a small set of unobserved variables (also called latent variables, or factors) which can account for the covariance among a larger set of observed variables (also called manifest variables). A factor is an unobservable variable that is assumed to influence observed variables. Scores on multiple tests may be indicators of intelligence (Spearman, 1904); political liberties and popular sovereignty may measure the quality of a country’s democracy (Bollen, 1980); or issue emphases in election manifestos may signify a political party’s underlying ideology (Gabel & Huber, 2000). Factor analysis is also used to assess the reliability and validity of measurement scales (Carmines & Zeller, 1979)

Fabrication of pyramidal probes with various periodic patterns and a single nanopore

The nanometer-scale patterned pyramidal probe with an electron beam-induced nanopore on the pyramid apex is an excellent candidate for an optical biosensor. The nanoapertures surrounded with various periodic groove patterns on the pyramid sides were fabricated using a focused ion beam technique, where the optical characteristics of the fabricated apertures with rectangular, circular, and elliptical groove patterns were investigated. The elliptical groove patterns on the pyramid were designed to maintain an identical distance between the grooves and the apex for the surface waves and, among the three patterns, the authors observed the highest optical transmission from the elliptically patterned pyramidal probe. A 103-fold increase of the transmitted optical intensity was observed after patterning with elliptical grooves, even without an aperture on the pyramid apex. The nanopore on the apex of the pyramid was fabricated using electron beam irradiation and was optically characterized

New record of Chromis weberi (Actinopterygii: Ovalentaria: Pomacentridae) from Jeju Island, southern Korea

Discovering tropical marine species outside of their distribution limits is important for evaluating the impact of climate change on marine ecosystems. One specimen (31.6 mm standard length) of a tropical fish, Chromis weberi Fowler et Bean, 1928, representing the family Pomacentridae, was first recorded from Jeju Island, Korea, on 8 December 2021. It was characterized by black posterior margins of the preopercle and opercle and black upper and lower lobes of the caudal fin. A specimen of this species collected from Munseom was distinguished from Chromis xanthura (Bleeker, 1854) based on distinct differences in the tips of the upper and lower caudal fin lobes, which are not black in C. xanthura. In addition, C. weberi was easily distinguished from the other four species in the genus Chromis, by the mitochondrial DNA cytochrome c oxidase subunit I gene sequence (345 bp), with genetic distances ranging from 0.130 to 0.252. This study documents the first record of C. weberi in temperate Korean waters, implying a poleward range expansion for this species. The Korean name ‘geom-eun-jeom-ggo-ri-ja-ri-dom’ has been proposed for C. weberi

EEG-controlled tele-grasping for undefined objects

This paper presents a teleoperation system of robot grasping for undefined objects based on a real-time EEG (Electroencephalography) measurement and shared autonomy. When grasping an undefined object in an unstructured environment, real-time human decision is necessary since fully autonomous grasping may not handle uncertain situations. The proposed system allows involvement of a wide range of human decisions throughout the entire grasping procedure, including 3D movement of the gripper, selecting proper grasping posture, and adjusting the amount of grip force. These multiple decision-making procedures of the human operator have been implemented with six flickering blocks for steady-state visually evoked potentials (SSVEP) by dividing the grasping task into predefined substeps. Each substep consists of approaching the object, selecting posture and grip force, grasping, transporting to the desired position, and releasing. The graphical user interface (GUI) displays the current substep and simple symbols beside each flickering block for quick understanding. The tele-grasping of various objects by using real-time human decisions of selecting among four possible postures and three levels of grip force has been demonstrated. This system can be adapted to other sequential EEG-controlled teleoperation tasks that require complex human decisions

Edge Breakdown Suppression of 10 Gbps Avalanche Photodiode

We have demonstrated a high-speed avalanche photodiode (APD) for a 10 Gbps optical communication system. To achieve a high gain-bandwidth product and reliable operation, the reduction of the multiplication layer thickness and an optimum design of the internal electric eld distribution are essential. One- and two-dimensional analysis were done for this purpose. The suppression of edge breakdown can be achieved by precise control of the thickness of the multiplication layer and charge densities of the eld control layer. Furthermore we suggest a junction curvature shape having negative curvature of the equi-potential line at the device edge. This new design successfully suppressed edge breakdown. The fabricated APD shows high current gain without premature edge breakdown, and a gain-bandwidth of above 80 GHz has been obtained