bluuebunny/crossref_metadata_2025_split huggingface dataset:
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Sums of Squares
Authors: Hershberger Scott L. 
Published: September 2005

Abstract
Whenever factorial designs have equal cell frequencies, the factors are orthogonal. Although orthogonal factors are not required, orthogonal factors permit a unique decomposition of the variance in the dependent variable. If cell frequencies vary, or there are empty cells, the factors are nonorthogonal: The variance decomposition of the dependent variable differs depending on which of Type I, II, III, or IV sums of squares is used for the analysis.
Normal Scores and Expected Order Statistics
Authors: Lunneborg Clifford E. 
Published: September 2005

Abstract
Rank tests replace raw scores with their ranks prior to computing a test statistic and its reference distribution. This use of ranks is advocated where the normality of the raw score observations is in doubt. An alternative approach is to replace the raw scores with values that resemble observations from a normal distribution more closely than do the integer‐spaced ranks, while taking the order of the raw scores into account. Permutation tests that are carried out following such a rank‐preserving transformation of the data is called a normal scores test.
Observational Study
Authors: Rosenbaum Paul R. 
Published: September 2005

AbstractAn observational study is an empiric investigation that attempts to estimate the effects caused by a treatment when it is not possible to perform an experiment. Random assignment of subjects to treatment or control in an experiment ensures that comparable groups of subjects are compared under alternative treatments. Without random assignment, in an observational study, the treatment and control groups may not be comparable prior to treatment, so that differing outcomes after treatment may not be effects caused by the treatment. Pretreatment differences that have been accurately measured are calledovert biases; they may often be controlled using analytical adjustments, such as matching, stratification, or covariance adjustment. Pretreatment differences that were not recorded are called hidden biases, and they pose substantial problems that must be addressed by other means. A well designed observational study permits detection of one or two of the most plausible hidden biases. The analysis of an observational study can measure the degree of sensitivity of conclusions to hidden biases of plausible magnitudes. Design strategies involving pattern specificity, such as Campbell's ‘multiple operationalism’ or Hill's dose‐response, may reduce sensitivity to hidden bias, and this possibility may be appraised using the design sensitivity of competing designs.
Parsimony/Occham's Razor
Authors: Mulaik Stanley A. 
Published: September 2005

Abstract
In modeling data, parsimony is the fewness of model parameters estimated relative to the number of data points fit by the model. The more parsimonious a model, the more degrees of freedom by which the model can fail to fit the data, thus making the model more potentially disconfirmable and more strongly supported when the model fits.
Placebo Effect
Authors: Onghena Patrick 
Published: September 2005

AbstractA placebo effect is conceptually defined as the beneficial effect associated with an intervention that does not include the presumed active ingredients. It can be operationally defined as the positive difference between the results of a placebo condition and a no‐treatment condition in a randomized trial. Placebos play a crucial role as a control in clinical medication trials, but discussion remains regarding their effect sizes and possible working mechanisms. As a confounding factor, a placebo effect is considered as a specific type of reactivity effect that should be distinguished from other confounding factors like history, spontaneous recovery, or statistical regression.
Population Stratification
Authors: van den Oord Edwin J. C. G. 
Published: September 2005

Abstract
In case‐control studies, population stratification can cause associations between marker alleles and disease status. These associations are ‘spurious’ because the marker is not informative about the location of a disease mutation. Family‐based tests are an important tool to avoid such spurious findings but the extent to which these tests are really needed is a topic of debate.
PValues
Authors: Dracup Chris 
Published: September 2005

AbstractThe advantages of reporting exactPvalues rather than using conventional significance levels are outlined. WhilePvalues do not represent the probability of truth of the null hypothesis, they do provide an index of the strength of evidence against that hypothesis. ThePvalue depends on whether the alternative hypothesis is one‐tailed or two‐tailed, with the two‐tailedPvalue generally being twice the one‐tailedPvalue. There is considerable debate about howPvalues for statistics with discrete distributions should be computed. In situations where the null hypothesis is known to be false,Pvalues provide useful information about the probability of error in the establishment of the direction of the true effect.
Randomization Based Tests
Authors: Ludbrook John 
Published: September 2005

Abstract
I argue that when an experiment in behavioral psychology is designed, it almost always involves taking a nonrandom sample and, by a process of randomization, dividing it into two or more ‘treatment’ groups. This places such experiments within the randomization model of inference, not the better‐known population model. The appropriate tests of significance under the randomization model are permutation (randomization) tests.
Rank Based Inference
Authors: Hettmansperger T. P. , McKean J. W. , Sheather S. J. 
Published: September 2005

Abstract
The use of ranks has a long history stretching back to 1945 with the seminal work of Wilcoxon. Early nonparametric rank tests were developed for the basic one‐ and two‐sample designs and then extended to the one‐ and two‐way layouts. These tests are popular because of their nonparametric property along with their good efficiency and robust properties. In this entry, we describe and illustrate how to extend rank‐based methods to the general linear model including regression, analysis of variance, and analysis of covariance. We also describe a coefficient of determination that is useful when assessing the fit of a model to the data.
R
asch Modeling
Authors: Fischer Gerhard H. 
Published: September 2005

Abstract

The Rasch Model is an item response model for ability or achievement tests with dichotomous item response format. Basic properties of the model are sufficiency of the raw score with respect to the person parameter and the so‐called ‘
specific objectivity
’ of comparisons between items and between persons. The model guarantees measurements with interval scale properties, except for very special cases where the scale becomes an ordered metric scale. The best‐founded approach to the estimation of the parameters of the model and to testing of fit or of other hypotheses about the parameters is the conditional likelihood method. Extensions of the model allow, for instance, to formalize structural hypotheses about the item parameters, to measure and test hypotheses about change, and to deal with scales composed of items with more than two ordered response categories.
Rater Agreement – Kappa
Authors: Mun Eun Young 
Published: September 2005

Abstract
Whether there is agreement or consensus among raters or observers on their evaluation of the objects of interest is one of the key questions in the behavioral sciences. One way to measure rater agreement is to have two raters make independent observations on the same group of objects, to classify them into a limited number of categories, and then to see to what extent the raters' evaluations overlap. Of all measures, Cohen's kappa (κ, 1960) is one of the best known and most frequently used measures to assess the extent of agreement by raters in a summary statement for entire observations.
Rater Agreement – Weighted Kappa
Authors: Mun Eun Young 
Published: September 2005

Abstract

One of the characteristics of Cohen's kappa (κ) is that any discrepancy between raters is equally weighted as zero. On the other hand, any agreement means
absolute agreement
between raters, and is equally weighted as one. Thus, the distinction between agreement and disagreement is categorical. For example, Table 1 from the Cohen's kappa section shows three agreement cells and six disagreement cells. In deriving Cohen's kappa, all six disagreement cells are treated equally. However, there could be situations in which the discrepancy between adjacent categories such as Categories 1 and 2 can be considered as partial agreement as opposed to complete disagreement. In those situations, Cohen's weighted kappa can be used to reflect the magnitude of agreement.
Reactivity
Authors: Onghena Patrick 
Published: September 2005

Abstract

Reactivity is a threat to the outcomes or treatments construct validity of observational and intervention studies that refers to the unintended reaction of participants on being observed or on being in a study. It is a threat to the
outcomes construct validity
if participants behave differently because they are aware that some aspect of their functioning is being observed or measured. It is a threat to the
treatments construct validity
if participants behave differently because they interpret the research or treatment setting in a way that makes the actual treatment different from the treatment as planned by the researcher. Because of the inevitable tendency of human participants to interact and give meaning to settings and their own and other's behavior, reactivity is a considerable risk to invalidity of both quasi‐ and randomized experiments in behavioral science.
Robust Statistics for Multivariate Methods
Authors: Victoria‐Feser Maria‐Pia 
Published: September 2005

AbstractRobust statistics deals with slightly misspecified models. When the data have not been generated exactly from the assumed models, robust procedures are by definition not (or very little) influenced by these model deviations. This is, in general, not the case with classical procedures such as least squares, maximum likelihood, and so on. Numerous multivariate models are based on the multivariate normal distribution, for which a relatively large number of robust procedures have been proposed. Most of the robust estimators are based on weighted means and covariances, and the weights are decreasing functions of the Mahalanobis distances. For nonnormal multivariate models, weights are more difficult to define, and more research is needed to develop robust procedures in these cases.
Receiver Operating Characteristics Curves
Authors: Wright Daniel B. 
Published: September 2005

Abstract

The receiver operating characteristic (ROC) curve is the principal graphical device for signal detection theory (SDT). It is generally used when there is a right or a wrong answer and participants provide some measure of confidence in their responses. The ROC is a scatterplot between the hit rate and the false alarm rate. Exploring this space allows the researcher to consider the differential value of hits and correct rejections (or of misses and false alarms). This is where ROCs have a big advantage over the alternatives. The main alternative,
logistic regression
, is based on similar mathematics. Historically, SDT/ROCs assumed normal distributions, but this is very similar to the logistic distributions, and most statistical packages allow either. The choice of approach rests largely on the form of graphical communication the researcher wants to use. While logistic regression focuses on discrimination, in SDT the researcher explicitly differentiates two types of accuracy: sensitivity and specificity. The ROC curve is an excellent tool for comparing these.
Sensitivity Analysis
Authors: Wakefield Jon 
Published: September 2005

AbstractIn an observational study, there is always the possibility of bias due to unmeasured variables, measurement error in explanatory variables and/or selection bias; and randomized studies are also not immune to at least some of these biases. A sensitivity analysis provides a means of asking a series of ‘what if?’ questions, in order to determine the robustness of the observed association to sources of bias.
Single‐Case Designs
Authors: Onghena Patrick 
Published: September 2005

Abstract
A single‐case design is an experimental design for a study in which one entity is observed repeatedly during a certain period under different levels of at least one independent variable. Single‐case designs have a long tradition and growing impact in behavioral science. They are the designs of first choice if demonstration of an effect in a single case is aimed at or if a test of a theory in a single case is sufficient (or the only possibility), and they are most compatible with clinical practice. The systematic and purposive planning of interventions in single‐case research represents the main difference with both observational time series research and qualitative case study research. In addition, single‐case research can gain internal and statistical‐conclusion validity by including randomization in the design. Two types of randomized single‐case designs are presented: randomized alternation designs and randomized phase designs. Finally, external validity of single‐case results can be demonstrated or tested by simultaneous or sequential replication and the corresponding simultaneous randomization tests and meta‐analytic procedures.
Reliability: Definitions and Estimation
Authors: Mead Alan D. 
Published: September 2005

Abstract

Reliability, ρ

XX
′

, is the degree to which test scores are precise and free from error. Classical test theory defines reliability as the ratio of true score variance to observed score variance:

. This article provides a comprehensive definition of reliability and then describes the methods by which reliability is commonly estimated, including their limitations. The article then discusses several closely‐related topics: the standard error of measurement; reliability in subpopulations; the Spearman‐Brown prophesy formula; true score correlations; reliability of speeded tests; and the relationship between classical reliability and item response theory information.
Covariance Matrices: Testing Equality of
Authors: Krzanowski Wojtek J. 
Published: September 2005

Abstract
Parametric multivariate inferential techniques make distributional assumptions about the data, and a common assumption in multisample problems is that dispersion matrices are equal in all the populations from which the samples have come. There is therefore need for a hypothesis test that can check on the adequacy of this assumption. In this article, we provide an appropriate test statistic, give its approximate (large sample) null distribution, illustrate its use on a small data set, and provide some cautionary comments about interpretation.
Transformation
Authors: Schmitt Neal 
Published: September 2005

Abstract
Transformations are systematic alterations to a set of scores that allow for application of various statistical procedures or better communication to readers. Transformations that often change the mean and standard deviation of a set of scores, but preserve the rank order and relative size of the distance between scores are linear; nonlinear transformations do not preserve these characteristics of the original data. Taking the square or square root or normalizing a set of scores are nonlinear transformations that make multivariate or parametric data analyses procedures more acceptable. Computing percentiles or T scores is often done to provide data in terms that are more easily understood by the statistically unsophisticated audiences.
Probability: An Introduction
Authors: Macdonald Ranald R. 
Published: September 2005

Abstract
The concept of a probability as a measure of the uncertainty of an event is introduced. Venn diagrams are shown to be useful as a means of representing probabilities and the basics of set theory are outlined. Treating relative frequencies as probabilities is justified using the law of large numbers and independence as a simplifying principle is explained with the help of conditional probabilities. Finally, a probability analysis is applied to a plausible real life situation.
Basic Protein Sequence Analysis
Authors: Krishnamurthy Nandini , Sjölander Kimmen V. 
Published: September 2005

AbstractPrediction of molecular function of proteins has become an important task in the genomics era. A wide variety of sequence analysis tools are available to biologists for this task. We have selected one or two primary protocols for tasks such as domain detection, subcellular localization, and motif detection. We also present a strategy for integration of results from different protocols. All the resources needed for these protocols are accessible via publicly available Web servers and databases and require little or no computational expertise.
Overview of Digital Electrophoresis Analysis
Authors: Medberry Scott , Gallagher Sean , Moomaw Butch 
Published: September 2005

AbstractGel electrophoresis has become a ubiquitous method in molecular biology for separating biomolecules. This prominence is the result of several factors, including the robustness, speed, and potentially high throughput of the technique. The results of this method are traditionally documented using silver halide‐based photography followed by manual interpretation. While this remains an excellent method for qualitative documentation of single‐gel results, digital capture offers a number of significant advantages when documentation requires quantitation and sophisticated analysis. Digital images of gel electropherograms can be obtained rapidly using an image‐capture device, and the images can be easily manipulated using image analysis software. This overview presents reasons for digital documentation and analysis, defines some important key terms for imaging, explains the capture process and reviews the devices used for image capture, and provides an introduction to the software and methods used for one‐ and two‐dimensional digital image analysis.
Visualization of Protein Interactions in Living Cells Using Bimolecular Fluorescence Complementation (BiFC) Analysis
Authors: Hu Chang‐Deng , Grinberg Asya V. , Kerppola Tom K. 
Published: September 2005

AbstractProtein interactions integrate stimuli from different signaling pathways and developmental programs. Bimolecular fluorescence complementation (BiFC) analysis has been developed for visualization of protein interactions in living cells. This approach is based on complementation between two fragments of a fluorescent protein when they are brought together by an interaction between proteins fused to the fragments, and it enables visualization of the subcellular locations of protein interactions in the normal cellular environment. It can be used for the analysis of many protein interactions and does not require information about the structures of the interaction partners. A multicolor BiFC approach has been developed for simultaneous visualization of interactions with multiple alternative partners in the same cell, based on complementation between fragments of engineered fluorescent proteins that produce bimolecular fluorescent complexes with distinct spectral characteristics. This enables comparison of subcellular distributions of different protein complexes in the same cell and allows analysis of competition between mutually exclusive interaction partners.
Measurement of Fcγ Receptor–Mediated Binding and Phagocytosis
Authors: Politis Alexander D. , Vogel Stefanie N. 
Published: September 2005

AbstractThis unit describes functional assays that quantify macrophage FcγR surface expression. In each assay, IgG‐opsonized sheep red blood cells (SRBC) labeled with Na251CrO4 are used to detect interaction with macrophages. The Basic Protocol measures phagocytosis of target cells following treatment of macrophages with agents known to modulate FcγR expression. The Alternate Protocol describes a method that can be used to measure FcγR‐mediated binding of target cells to macrophages. A choice of opsonin in both methods allows for some discrimination between subclasses of FcγRs that are responsible for the observed results.
Asymmetric Aza‐MoritaBaylisHillman Reaction of N‐Sulfonated Imines with Methyl Vinyl Ketone Catalyzed by Chiral Phosphine Lewis Bases Bearing Perfluoroalkanes as “Pony Tails”
Authors: Shi Min , Chen Lian‐Hui , Teng Wen‐Dong 
Published: September 2005

AbstractIn the aza‐Morita–BaylisHillman reaction of N‐sulfonated imines (N‐arylmethylidene‐4‐methylbenzenesulfonamides and others) with methyl vinyl ketone (MVK), we found that in the presence of a catalytic amount of the chiral phosphine Lewis bases (R)‐(−)‐6,6′‐bis[tris(3,3,4,4,5,5,6,6,7,7,8,8,8‐tridecafluorooctyl)silyl]‐2′‐(diphenylphosphanyl)‐[1,1′]binaphthalenyl‐2‐ol LB2 and (R)‐(−)‐6,6′‐(3,3,4,4,5, 5,6,6,7,7,8,8,8‐tridecafluorooctyl) ‐2′‐(diphenylphosphanyl)‐[1,1′]binaphthalenyl‐2‐ol LB3 bearing two perfluoroalkane chains at 6,6′‐positions of the naphthalene framework, the corresponding adducts could be obtained in good yields with good to high ee (52–95% ee) at room temperature (15 °C) or low temperature (−20 °C) in THF, respectively. LB3 is more effective in this reaction than the previously reported original chiral phosphine Lewis base (R)‐(−)‐2′‐diphenylphosphanyl‐[1,1′]binaphthalenyl‐2‐ol LB1.
Palladium‐Catalysed Enantioselective Conjugate Addition of Aromatic Amines to α,β‐Unsaturated N‐Imides. Effect of the Chelating Moiety
Authors: Phua Pim Huat , de Vries Johannes G. , Hii King Kuok (Mimi) 
Published: September 2005

AbstractPalladium‐catalysed enantioselective additions of aromatic amines to α,β‐unsaturated N‐imides 4–6 are reported. The N‐substituent of the Michael acceptor appears to have an unusual modulating effect on the amine activity. The effects of introducing different substituents are examined. Overall, the yield and selectivity of the system appear to be less sensitive to environmental effects than previous systems. The importance of the counteranion is revealed.
Synthesis of an Enantiocomplementary Catalyst of β‐Isocupreidine (β‐ICD) from Quinine
Authors: Nakano Ayako , Ushiyama Mina , Iwabuchi Yoshiharu , Hatakeyama Susumi 
Published: September 2005

AbstractCompound 20, a pseudoenantiomer of β‐isocupreidine (β‐ICD), was synthesized from quinine employing a Barton reaction of nitrosyl ester 13 and acid‐catalyzed cyclization of carbinol 18 as key steps. The Baylis–Hillman reaction of benzaldehyde, p‐nitrobenzaldehyde, and hydrocinnamaldehyde with 1,1,1,3,3,3‐hexafluoroisopropyl acrylate (HFIPA) using 20 as a chiral amine catalyst was found to give the corresponding S‐enriched adducts in high optical purity (>91% ee) in contrast to the β‐ICD‐catalyzed reaction which affords R‐enriched adducts. This result suggests that compound 20 can serve as an enantiocomplementary catalyst of β‐ICD in the asymmetric Baylis–Hillman reaction of aldehydes with HFIPA.
Airborne laser altimetry in alluviated landscapes
Authors: Challis Keith 
Published: September 2005

AbstractScanning airborne laser altimetry, usually referred to as LiDAR, generates high spatial resolution, high accuracy elevation data. The technique has found considerable use in the earth sciences, for example for flood modelling and prediction. This paper examines some geoarchaeological applications for LiDAR in alluviated landscapes. The LiDAR data for several lowland river valleys in England are examined. The technique has considerable potential for identifying archaeologically significant geomorphological features through examination of the microtopography of floodplain and terrace surfaces and for mapping upstanding archaeological earthworks. Copyright © 2005 John Wiley & Sons, Ltd.