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Significance Test (significance + test)
Selected AbstractsImpact of a multiyear professional development intervention on science achievement of culturally and linguistically diverse elementary studentsJOURNAL OF RESEARCH IN SCIENCE TEACHING, Issue 6 2008Okhee Lee Abstract This study examined the impact of the 3-year implementation of a professional development intervention on science achievement of culturally and linguistically diverse elementary students. Teachers were provided with instructional units and workshops that were designed to improve teaching practices and foster positive beliefs about science and literacy with diverse student groups. The study involved third, fourth, and fifth grade students at six elementary schools in a large urban school district during the 2001 through 2004 school years. Significance tests of mean scores between pre- and posttests indicated statistically significant increases each year on all measures of science at all three grade levels. Achievement gaps among demographic subgroups sometimes narrowed among fourth grade students and remained consistent among third and fifth grade students. Item-by-item comparisons with NAEP and TIMSS samples indicated overall positive performance by students at the end of each school year. The consistent patterns of positive outcomes indicate the effectiveness of our intervention in producing achievement gains at all three grade levels while also reducing achievement gaps among demographic subgroups at the fourth grade. © 2008 Wiley Periodicals, Inc. J Res Sci Teach 45: 726,747, 2008 [source] Reassessing the impact of North Atlantic Oscillation on the sub-Saharan vegetation productivityGLOBAL CHANGE BIOLOGY, Issue 4 2003GUILING WANG Abstract The Northern Atlantic Oscillation (NAO) has been shown to have a significant impact on the terrestrial ecosystem in the Sahelian region of Africa during the 1980s, and it has been strongly suggested that NAO may be a reliable predictor for the response of the Sahelian ecosystem to global climate variability. Using data from an extended period, we provide a reassessment for the impact of NAO on the Sahelian climate and ecosystem, and show that there is no consistent relationship between NAO and the ecosystem over Sahel. Statistical analysis on the NAO, vegetation, and precipitation data indicates that NAO influences the Sahelian vegetation productivity exclusively through its impact on precipitation. However, the relationship between the NAO index and Sahelian precipitation varies substantially with time. The correlation coefficient fluctuates between positive and negative values, and does not pass the 5% significance test during most of the twentieth century. The NAO system, although documented to govern the ecosystem dynamics over many other regions, does not have a consistent impact on the ecosystem over the Sahel. Therefore, the NAO index cannot produce a useful prediction on the ecosystem variability and changes in this region. This study provides an example that correlations based on short climate and ecological records (less than 20 years in this case) can be spurious and potentially misleading. [source] On Making Progress in Communication ScienceHUMAN COMMUNICATION RESEARCH, Issue 4 2002Franklin J. Boster This essay advances practices for designing, analyzing, and reporting communication research. The arguments presented center around improving researchers' abilities to cumulate results across studies, but also apply to improving the utility of the individual study. Practices advocated include: (a) sophistication, falsification, and replication as important criteria for evaluating research design; (b) diminishing the importance of the null hypothesis statistical significance test, employing confidence intervals, and correcting correlations for both measurement error and range restriction when analyzing data; and (c) including both descriptive statistics and measures of the strength of bivariate relationships when reporting results. [source] Are Mechanistic and Statistical QSAR Approaches Really Different?MOLECULAR INFORMATICS, Issue 6-7 2010MLR Studies on 158 Cycloalkyl-Pyranones Abstract Two parallel approaches for quantitative structure-activity relationships (QSAR) are predominant in literature, one guided by mechanistic methods (including read-across) and another by the use of statistical methods. To bridge the gap between these two approaches and to verify their main differences, a comparative study of mechanistically relevant and statistically relevant QSAR models, developed on a case study of 158 cycloalkyl-pyranones, biologically active on inhibition (Ki) of HIV protease, was performed. Firstly, Multiple Linear Regression (MLR) based models were developed starting from a limited amount of molecular descriptors which were widely proven to have mechanistic interpretation. Then robust and predictive MLR models were developed on the same set using two different statistical approaches unbiased of input descriptors. Development of models based on Statistical I method was guided by stepwise addition of descriptors while Genetic Algorithm based selection of descriptors was used for the Statistical II. Internal validation, the standard error of the estimate, and Fisher's significance test were performed for both the statistical models. In addition, external validation was performed for Statistical II model, and Applicability Domain was verified as normally practiced in this approach. The relationships between the activity and the important descriptors selected in all the models were analyzed and compared. It is concluded that, despite the different type and number of input descriptors, and the applied descriptor selection tools or the algorithms used for developing the final model, the mechanistical and statistical approach are comparable to each other in terms of quality and also for mechanistic interpretability of modelling descriptors. Agreement can be observed between these two approaches and the better result could be a consensus prediction from both the models. [source] Understanding statistical analysis in the surgical literature: some key conceptsANZ JOURNAL OF SURGERY, Issue 5 2009Jane Young Abstract Understanding the fundamentals of statistical analysis allows surgeons to evaluate the logic and validity of statistical methods presented in published papers in order to make a judgement about the quality of the reported findings. This paper presents an overview of some basic concepts, with an emphasis on principles rather than on mathematical detail, which relate to selecting the correct statistical test and interpreting the results of statistical analysis. The most important factor in determining the appropriate significance test is the type of outcome data that have been collected. A significance test is used to calculate a probability (P) value, which is a measure of the strength of the effect seen in the study, but additional useful information is obtained from confidence intervals that indicate not only the size and direction of the effect but also the precision of the study. Judgements about the clinical importance of a result should be based on the size of the effect seen rather than the P value, as the latter is strongly influenced by the size of the study. [source] A simulation approach to determine statistical significance of species turnover peaks in a species-rich tropical cloud forestDIVERSITY AND DISTRIBUTIONS, Issue 6 2007K. Bach ABSTRACT Use of ,-diversity indices in the study of spatial distribution of species diversity is hampered by the difficulty of applying significance tests. To overcome this problem we used a simulation approach in a study of species turnover of ferns, aroids, bromeliads, and melastomes along an elevational gradient from 1700 m to 3400 m in a species-rich tropical cloud forest of Bolivia. Three parameters of species turnover (number of upper/lower elevational species limits per elevational step, Wilson,Shmida similarity index between adjacent steps) were analysed. Significant species turnover limits were detected at 2000 (± 50) m and 3050 m, which roughly coincided with the elevational limits of the main vegetation types recognized in the study area. The taxon specificity of elevational distributions implies that no single plant group can be used as a reliable surrogate for overall plant diversity and that the response to future climate change will be taxon-specific, potentially leading to the formation of plant communities lacking modern analogues. Mean elevational range size of plant species was 490 m (± 369). Elevational range sizes of terrestrial species were shorter than those of epiphytes. We conclude that our simulation approach provides an alternative approach for assessing the statistical significance of levels of species turnover along ecological gradient without the limitations imposed by traditional statistical approaches. [source] "What exactly are you inferring?"ENVIRONMENTAL TOXICOLOGY & CHEMISTRY, Issue 5 2008A closer look at hypothesis testing Abstract This critical review describes the confused application of significance tests in environmental toxicology and chemistry that often produces incorrect inferences and indefensible regulatory decisions. Following a brief review of statistical testing theory, nine recommendations are put forward. The first is that confidence intervals be used instead of hypothesis tests whenever possible. The remaining recommendations are relevant if hypothesis tests are used. They are as follows: Define and justify Type I and II error rates a priori; set and justify an effect size a priori; do not confuse p(E | H0) and p(H0 | E); design tests permitting Positive Predictive Value estimation; publish negative results; estimate a priori, not post hoc, power; as warranted by study goals, favor null hypotheses that are not conventional nil hypotheses; and avoid definitive inferences from isolated tests. [source] Description of growth by simple versus complex models for Baltic Sea spring spawning herringJOURNAL OF APPLIED ICHTHYOLOGY, Issue 1 2001J. Gröger The objective was to find a length,growth model to help differentiate between herring stocks (Clupea harengus l.) when their length,growth shows systematically different patterns. The most essential model restriction was that it should react robustly against variations in the underlying age range which varies not only over time but also between the different herring stocks. Because of the limited age range, significance tests as well as confidence intervals of the model parameters should allow a small sample restriction. Thus, parameter estimation should be of an analytical rather than asymptotic nature and the model should contain a minimum set of parameters. The article studies the comparative characteristics of a simple non-asymptotic two-parameter growth model (allometric length,growth function, abbreviated as ALG model) in contrast to higher parametric and more complex growth models (logistic and von-Bertalanffy growth functions, abbreviated as LGF and VBG models). An advantage of the ALG model is that it can be easily linearized and the growth coefficients can be directly derived as regression parameters. The intrinsic ALG model linearity makes it easy to test restrictions (normality, homoscedasticity and serial uncorrelation of the error term) and to formulate analytic confidence intervals. The ALG model features were exemplified and validated by a 1995 Baltic spring spawning herring (BSSH) data set that included a 12-year age range. The model performance was compared with that of the logistic and the von-Bertalanffy length,growth curves for different age ranges and by means of various parameter estimation techniques. In all cases the ALG model performed better and all ALG model restrictions (no autocorrelation, homoscedasticity, and normality of the error term) were fulfilled. Furthermore, all findings seemed to indicate a pseudo-asymptotic growth for BSSH. The proposed model was explicitly derived for of herring length-growth; the results thus should not be generalized interspecifically without additional proof. [source] Testing for Neglected Nonlinearity in Cointegrating Relationships,JOURNAL OF TIME SERIES ANALYSIS, Issue 6 2007Andrew P. Blake C32; C45 Abstract., This article proposes pure significance tests for the absence of nonlinearity in cointegrating relationships. No assumption of the functional form of the nonlinearity is made. It is envisaged that the application of such tests could form the first step towards specifying a nonlinear cointegrating relationship for empirical modelling. The asymptotic and small sample properties of our tests are investigated, where special attention is paid to the role of nuisance parameters and a potential resolution using the bootstrap. [source] Statistical Tests for ClonalityBIOMETRICS, Issue 2 2007Colin B. Begg Summary Cancer investigators frequently conduct studies to examine tumor samples from pairs of apparently independent primary tumors with a view to determine whether they share a "clonal" origin. The genetic fingerprints of the tumors are compared using a panel of markers, often representing loss of heterozygosity (LOH) at distinct genetic loci. In this article we evaluate candidate significance tests for this purpose. The relevant information is derived from the observed correlation of the tumors with respect to the occurrence of LOH at individual loci, a phenomenon that can be evaluated using Fisher's exact test. Information is also available from the extent to which losses at the same locus occur on the same parental allele. Data from these combined sources of information can be evaluated using a simple adaptation of Fisher's exact test. The test statistic is the total number of loci at which concordant mutations occur on the same parental allele, with higher values providing more evidence in favor of a clonal origin for the two tumors. The test is shown to have high power for detecting clonality for plausible models of the alternative (clonal) hypothesis, and for reasonable numbers of informative loci, preferably located on distinct chromosomal arms. The method is illustrated using studies to identify clonality in contralateral breast cancer. Interpretation of the results of these tests requires caution due to simplifying assumptions regarding the possible variability in mutation probabilities between loci, and possible imbalances in the mutation probabilities between parental alleles. Nonetheless, we conclude that the method represents a simple, powerful strategy for distinguishing independent tumors from those of clonal origin. [source] | |||||||||||||