The role of analogy in spelling in English primary school children - a partial intervention study

The English writing system is notoriously irregular in its orthography at the phonemic level. It was therefore proposed that focusing beginner-spellers’ attention on sound-letter relations at the sub-syllabic level might improve spelling performance. This hypothesis was tested in Experiments 1 and 2 using a ‘clue word’ paradigm to investigate the effect of analogy teaching intervention / non-intervention on the spelling performance of an experimental group and controls. The results overall showed the intervention to be effective in improving spelling, and this effect to be enduring. Experiment 3 demonstrated a greater application of analogy in spelling, when clue words, which participants used in analogy to spell test words, remained in view during testing. A series of regression analyses, with spelling entered as the criterion variable and age, analogy and phonological plausibility (PP) as predictors, showed both analogy and PP to be highly predictive of spelling. Experiment 4 showed that children could use analogy to improve their spelling, even without intervention, by comparing their performance in spelling words presented in analogous categories or in random lists. Consideration of children’s patterns of analogy use at different points of development showed three age groups to use similar patterns of analogy, but contrasting analogy patterns for spelling different words. This challenges stage theories of analogy use in literacy. Overall the most salient units used in analogy were the rime and, to a slightly lesser degree, the onset-vowel and vowel. Finally, Experiment 5 showed analogy and phonology to be fairly equally influential in spelling, but analogy to be more influential than phonology in reading. Five separate experiments therefore found analogy to be highly influential in spelling. Experiment 5 also considered the role of memory and attention in literacy attainment. The important implications of this research are that analogy, rather than purely phonics-based strategy, is instrumental in correct spelling in English.

Statnote 25: Stepwise multiple regression

An investigator may also wish to select a small subset of the X variables which give the best prediction of the Y variable. In this case, the question is how many variables should the regression equation include? One method would be to calculate the regression of Y on every subset of the X variables and choose the subset that gives the smallest mean square deviation from the regression. Most investigators, however, prefer to use a ‘stepwise multiple regression’ procedure. There are two forms of this analysis called the ‘step-up’ (or ‘forward’) method and the ‘step-down’ (or ‘backward’) method. This Statnote illustrates the use of stepwise multiple regression with reference to the scenario introduced in Statnote 24, viz., the influence of climatic variables on the growth of the crustose lichen Rhizocarpon geographicum (L.)DC.

Statnote 32 : the partial correlation coefficient

In previous statnotes, the application of correlation and regression methods to the analysis of two variables (X,Y) was described. The most important statistic used to measure the degree of correlation between two variables is Pearson’s ‘product moment correlation coefficient’ (‘r’). The correlation between two variables may be due to their common relation to other variables. Hence, investigators using correlation studies need to be alert to the possibilities of spurious correlation and the methods of ‘partial correlation’ are one method of taking this into account. This statnote applies the methods of partial correlation to three scenarios. First, to a fairly obvious example of a spurious correlation resulting from the ‘size effect’ involving the relationship between the number of general practitioners (GP) and the number of deaths of patients in a town. Second, to the relationship between the abundance of the nitrogen-fixing bacterium Azotobacter in soil and three soil variables, and finally, to a more complex scenario, first introduced in Statnote 24involving the relationship between the growth of lichens in the field and climate.

Regression analysis of ranked segment parameters for optic nerve head classification:a pilot study

Purpose: To determine whether curve-fitting analysis of the ranked segment distributions of topographic optic nerve head (ONH) parameters, derived using the Heidelberg Retina Tomograph (HRT), provide a more effective statistical descriptor to differentiate the normal from the glaucomatous ONH. Methods: The sample comprised of 22 normal control subjects (mean age 66.9 years; S.D. 7.8) and 22 glaucoma patients (mean age 72.1 years; S.D. 6.9) confirmed by reproducible visual field defects on the Humphrey Field Analyser. Three 10°-images of the ONH were obtained using the HRT. The mean topography image was determined and the HRT software was used to calculate the rim volume, rim area to disc area ratio, normalised rim area to disc area ratio and retinal nerve fibre cross-sectional area for each patient at 10°-sectoral intervals. The values were ranked in descending order, and each ranked-segment curve of ordered values was fitted using the least squares method. Results: There was no difference in disc area between the groups. The group mean cup-disc area ratio was significantly lower in the normal group (0.204 ± 0.16) compared with the glaucoma group (0.533 ± 0.083) (p < 0.001). The visual field indices, mean deviation and corrected pattern S.D., were significantly greater (p < 0.001) in the glaucoma group (-9.09 dB ± 3.3 and 7.91 ± 3.4, respectively) compared with the normal group (-0.15 dB ± 0.9 and 0.95 dB ± 0.8, respectively). Univariate linear regression provided the best overall fit to the ranked segment data. The equation parameters of the regression line manually applied to the normalised rim area-disc area and the rim area-disc area ratio data, correctly classified 100% of normal subjects and glaucoma patients. In this study sample, the regression analysis of ranked segment parameters method was more effective than conventional ranked segment analysis, in which glaucoma patients were misclassified in approximately 50% of cases. Further investigation in larger samples will enable the calculation of confidence intervals for normality. These reference standards will then need to be investigated for an independent sample to fully validate the technique. Conclusions: Using a curve-fitting approach to fit ranked segment curves retains information relating to the topographic nature of neural loss. Such methodology appears to overcome some of the deficiencies of conventional ranked segment analysis, and subject to validation in larger scale studies, may potentially be of clinical utility for detecting and monitoring glaucomatous damage. © 2007 The College of Optometrists.

Theoretical Hyperbolic Model of a Partial Agonism: Explicit Formulas for Affinity, Efficacy and Amplification

The quantitative analysis of receptor-mediated effect is based on experimental concentration-response data in which the independent variable, the concentration of a receptor ligand, is linked with a dependent variable, the biological response. The steps between the drug–receptor interaction and the subsequent biological effect are to some extent unknown. The shape of the fitting curve of the experimental data may give some in-sights into the nature of the concentration–receptor–response (C-R-R) mechanism. It can be evaluated by non-linear regression analysis of the experimental data points of the independent and dependent variables, which could be considered as a history of the interaction between the drug and receptors. However, this information is not enough to evaluate such important parameters of the mechanism as the dissociation constant (affinity) and efficacy. There are two ways to provide more detailed information about the C-R-R mechanism: (i) an experimental way for obtaining data with new or

Strong Consistency of the Conditional Least Squares Estimator for a Nonstationary Process. Example of the Garch Model

2000 Mathematics Subject Classification: Primary: 62M10, 62J02, 62F12, 62M05, 62P05, 62P10; secondary: 60G46, 60F15.

On the Lp-Norm Regression Models for Estimating Value-at-Risk

Analysis of risk measures associated with price series data movements and its predictions are of strategic importance in the financial markets as well as to policy makers in particular for short- and longterm planning for setting up economic growth targets. For example, oilprice risk-management focuses primarily on when and how an organization can best prevent the costly exposure to price risk. Value-at-Risk (VaR) is the commonly practised instrument to measure risk and is evaluated by analysing the negative/positive tail of the probability distributions of the returns (profit or loss). In modelling applications, least-squares estimation (LSE)-based linear regression models are often employed for modeling and analyzing correlated data. These linear models are optimal and perform relatively well under conditions such as errors following normal or approximately normal distributions, being free of large size outliers and satisfying the Gauss-Markov assumptions. However, often in practical situations, the LSE-based linear regression models fail to provide optimal results, for instance, in non-Gaussian situations especially when the errors follow distributions with fat tails and error terms possess a finite variance. This is the situation in case of risk analysis which involves analyzing tail distributions. Thus, applications of the LSE-based regression models may be questioned for appropriateness and may have limited applicability. We have carried out the risk analysis of Iranian crude oil price data based on the Lp-norm regression models and have noted that the LSE-based models do not always perform the best. We discuss results from the L1, L2 and L∞-norm based linear regression models. ACM Computing Classification System (1998): B.1.2, F.1.3, F.2.3, G.3, J.2.

Estimation of average annual daily traffic (AADT) using geographically weighted regression (GWR) method and geographic information system (GIS)

Annual average daily traffic (AADT) is important information for many transportation planning, design, operation, and maintenance activities, as well as for the allocation of highway funds. Many studies have attempted AADT estimation using factor approach, regression analysis, time series, and artificial neural networks. However, these methods are unable to account for spatially variable influence of independent variables on the dependent variable even though it is well known that to many transportation problems, including AADT estimation, spatial context is important. ^ In this study, applications of geographically weighted regression (GWR) methods to estimating AADT were investigated. The GWR based methods considered the influence of correlations among the variables over space and the spatially non-stationarity of the variables. A GWR model allows different relationships between the dependent and independent variables to exist at different points in space. In other words, model parameters vary from location to location and the locally linear regression parameters at a point are affected more by observations near that point than observations further away. ^ The study area was Broward County, Florida. Broward County lies on the Atlantic coast between Palm Beach and Miami-Dade counties. In this study, a total of 67 variables were considered as potential AADT predictors, and six variables (lanes, speed, regional accessibility, direct access, density of roadway length, and density of seasonal household) were selected to develop the models. ^ To investigate the predictive powers of various AADT predictors over the space, the statistics including local r-square, local parameter estimates, and local errors were examined and mapped. The local variations in relationships among parameters were investigated, measured, and mapped to assess the usefulness of GWR methods. ^ The results indicated that the GWR models were able to better explain the variation in the data and to predict AADT with smaller errors than the ordinary linear regression models for the same dataset. Additionally, GWR was able to model the spatial non-stationarity in the data, i.e., the spatially varying relationship between AADT and predictors, which cannot be modeled in ordinary linear regression. ^

Angular distribution of Z(0 power) bosons in Z+jet events at the square root of S = 7 TeV

For the first time, the Z0 boson angular distribution in the center-of-momentum frame is measured in proton-proton collisions at [special characters omitted] = 7 TeV at the CERN LHC. The data sample, recorded with the CMS detector, corresponds to an integrated luminosity of approximately 36 pb–1 . Events in which there is a Z0 and at least one jet, with a jet transverse momentum threshold of 20 GeV and absolute jet rapidity less than 2.4, are selected for the analysis. Only the Z0's muon decay channel is studied. Within experimental and theoretical uncertainties, the measured angular distribution is in agreement with next-to-leading order perturbative QCD predictions.

The relationship of managers' self -reported leadership practices and their spirituality

The role of spirituality in leadership in business and other organizations has gained growing recognition. The purpose of this study was to explore the relationship between spirituality and nine selected transformational leadership practices. Community leaders (N = 138) in business, education, and other professions who were graduates of a 10-week leadership program, Leadership Fort Lauderdale, from 1994 to 2004 completed the Spirituality Assessment Scale (SAS), the Leadership Practices Inventory (LPI), and four transformational leadership items of the Multifactor Leadership Questionnaire (MLQ). ^ The predictor variables were participants' scores on the LPI and MLQ. The criterion variable was their score on the SAS. Stepwise multiple regression analysis was used to test the hypothesis: Is there a combination of nine selected transformational leadership practices that would account for a significant portion of the variance of each of two spirituality measures? The Definitive and Correlated dimensions and Total spirituality score of the SAS were used in the analysis. ^ Results showed that two of the LPI leadership practices were significantly related to spirituality. The variable Inspiring a Shared Vision accounted for 10% of the variance of the SAS Definitive dimension. The variable Encouraging the Heart accounted for 30% of the variance of the Correlated dimension. For the Total spirituality score, two models were revealed. In the first model, Encouraging the Heart accounted for 28% of the variance of the total spirituality score. In the second model, Encouraging the Heart and Inspiring a Shared Vision together accounted for 31% of the total spirituality score. None of the transformational leadership practices from the MLQ were significantly related to spirituality. ^ The data partially support the hypothesis: two of the nine leadership variables did in combination correlate with leaders' spirituality. The results also support at least a partial relationship between spirituality and certain transformational leadership practices among leaders in various spheres, such as education, business, and other professions. ^

Comparison of Some Improved Estimators for Linear Regression Model under Different Conditions

Multiple linear regression model plays a key role in statistical inference and it has extensive applications in business, environmental, physical and social sciences. Multicollinearity has been a considerable problem in multiple regression analysis. When the regressor variables are multicollinear, it becomes difficult to make precise statistical inferences about the regression coefficients. There are some statistical methods that can be used, which are discussed in this thesis are ridge regression, Liu, two parameter biased and LASSO estimators. Firstly, an analytical comparison on the basis of risk was made among ridge, Liu and LASSO estimators under orthonormal regression model. I found that LASSO dominates least squares, ridge and Liu estimators over a significant portion of the parameter space for large dimension. Secondly, a simulation study was conducted to compare performance of ridge, Liu and two parameter biased estimator by their mean squared error criterion. I found that two parameter biased estimator performs better than its corresponding ridge regression estimator. Overall, Liu estimator performs better than both ridge and two parameter biased estimator.

Online Education, Accrediting Standards, and Student Success: An Examination of the Relationship Between the Southern Association of Colleges and Schools Commission on Colleges Standards for Online Education and Student Success

Prior to 2000, there were less than 1.6 million students enrolled in at least one online course. By fall 2010, student enrollment in online distance education showed a phenomenal 283% increase to 6.1 million. Two years later, this number had grown to 7.1 million. In light of this significant growth and skepticism about quality, there have been calls for greater oversight of this format of educational delivery. Accrediting bodies tasked with this oversight have developed guidelines and standards for online education. There is a lack of empirical studies that examine the relationship between accrediting standards and student success. The purpose of this study was to examine the relationship between the presence of Southern Association of Colleges and Schools Commission on College (SACSCOC) standards for online education in online courses, (a) student support services and (b) curriculum and instruction, and student success. An original 24-item survey with an overall reliability coefficient of .94 was administered to students (N=464) at Florida International University, enrolled in 24 university-wide undergraduate online courses during fall 2014, who rated the presence of these standards in their online courses. The general linear model was utilized to analyze the data. The results of the study indicated that the two standards, student support services and curriculum and instruction were both significantly and positively correlated with student success but with small R2 and strengths of association less than .35 and .20 respectively. Mixed results were produced from Chi-square tests for differences in student success between higher and lower rated online courses when controlling for various covariates such as discipline, gender, race/ethnicity, GPA, age, and number of online courses previously taken. A multiple linear regression analysis revealed that the curriculum and instruction standard was the only variable that accounted for a significant amount of unique variance in student success. Another regression test revealed that no significant interaction effect exists between the two SACSCOC standards and GPA in predicting student success. The results of this study are useful for administrators, faculty, and researchers who are interested in accreditation standards for online education and how these standards relate to student success.

Nutritional status of lactating mothers and their children 6-23 months of age in pre- and post-harvest seasons in two agro-ecological zones of rural Ethiopia

The objective of this study was to assess seasonal variation in nutritional status and feeding practices among lactating mothers and their children 6-23 months of age in two different agro-ecological zones of rural Ethiopia (lowland zone and midland zone). Food availability and access are strongly affected by seasonality in Ethiopia. However, there are few published data on the effects of seasonal food fluctuations on nutritional status and dietary diversity patterns of mothers and children in rural Ethiopia. A longitudinal study was conducted among 216 mothers in two agro-ecological zones of rural Ethiopia during pre and post-harvest seasons. Data were collected on many parameters including anthropometry, blood levels of haemoglobin and ferritin and zinc, urinary iodine levels, questionnaire data regarding demographic and household parameters and health issues, and infant and young child feeding practices, 24 h food recall to determine dietary diversity scores, and household use of iodized salt. Chi-square and multivariable regression models were used to identify independent predictors of nutritional status. A wide variety of results were generated including the following highlights. It was found that 95.4% of children were breastfed, of whom 59.7% were initially breastfed within one hour of birth, 22.2% received pre-lacteal feeds, and 50.9% of children received complementary feedings by 6 months of age. Iron deficiency was found in 44.4% of children and 19.8% of mothers. Low Zinc status was found in 72.2% of children and 67.3% of mothers. Of the study subjects, 52.5% of the children and 19.1% of the mothers were anaemic, and 29.6% of children and 10.5% of mothers had iron deficiency anaemia. Among the mothers with low serum iron status, 81.2% and 56.2% of their children had low serum zinc and iron, respectively. Similarly, among the low serum zinc status mothers, 75.2% and 45.3% of their children had low serum in zinc and iron, respectively. There was a strong correlation between the micronutrient status of the mothers and the children for ferritin, zinc and haemoglobin (P <0.001). There was also statistically significant difference between agro-ecological zones for micronutrient deficiencies among the mothers (p<0.001) but not for their children. The majority (97.6%) of mothers in the lowland zone were deficient in at least one micronutrient biomarker (zinc or ferritin or haemoglobin). Deficiencies in one, two, or all three biomarkers of micronutrient status were observed in 48.1%, 16.7% and 9.9% of mothers and 35.8%, 29.0%, and 23.5%, of children, respectively. Additionally, about 42.6% of mothers had low levels of urinary iodine and 35.2% of lactating mothers had goitre. Total goitre prevalence rates and urinary iodine levels of lactating mothers were not significantly different across agro-ecological zones. Adequately iodised salt was available in 36.6% of households. The prevalence of anaemia increased from post-harvest (21.8%) to pre-harvest seasons (40.9%) among lactating mothers. Increases were from 8.6% to 34.4% in midland and from 34.2% to 46.3% in lowland agro-ecological zones. Fifteen percent of mothers were anaemic during both seasons. Predictors of anaemia were high parity of mother and low dietary diversity. The proportion of stunted and underweight children increased from 39.8% and 27% in post-harvest season to 46.0% and 31.8% in pre-harvest season, respectively. However, wasting in children decreased from 11.6% to 8.5%. Major variations in stunting and underweight were noted in midland compared to lowland agroecological zones. Anthropometric measurements in mothers indicated high levels of undernutrition. The prevalence of undernutrition in mothers (BMI <18.5kg/m2) increased from 41.7 to 54.7% between post- and pre-harvest seasons. The seasonal effect was generally higher in the midland community for all forms of malnutrition. Parity, number of children under five years and regional variation were predictors of low BMI among lactating mothers. There were differences in minimum meal frequency, minimum acceptable diet and dietary diversity in children in pre-harvest and post-harvest seasons and these parameters were poor in both seasons. Dietary diversity among mothers was higher in lowland zone but was poor in both zones across the seasons. In conclusion, malnutrition and micronutrient deficiencies are very prevalent among lactating mothers and their children 6-23 months old in the study areas. There are significant seasonal variations in malnutrition and dietary diversity, in addition to significant differences between lowland and midland agro-ecological zones. These findings suggest a need to design effective preventive public health nutrition programs to address both the mothers’ and children’s needs particularly in the preharvest season.

The association between parental attitudes and alcohol consumption and adolescent alcohol consumption in Southern Ireland: a cross-sectional study

Background: Alcohol plays a complex role in society. A recent study showed that over half of Irish adults drink hazardously. Adolescents report increased levels of alcohol consumption. Previous research has inferred the influence of the parent on their adolescent. Thus, the aim of the current study was to investigate the association between adolescent alcohol consumption and their parent’s consumption pattern and attitude toward alcohol use in Southern Ireland. Methods: A cross-sectional survey was undertaken in November 2014. This involved distributing a survey to adolescents (n = 982) in their final two years of second level education and at least one of their parents from a local electorate area in Southern Ireland. This survey included: alcohol use, self- reported height and weight, smoking status, mental health and well-being along with attitudinal questions. Chi-square tests and multivariate logistic regression were utilised. Results: A 37 % response rate was achieved. Over one-third (34.2 %) of adolescents and 47 % of parents surveyed reported hazardous drinking. Over 90 % of parents disagreed with allowing their adolescent to get drunk and rejected the idea that getting drunk is part of having fun as an adolescent. The majority (79.5 %) of parents surveyed believed that their alcohol consumption pattern set a good example for their adolescent. Multivariate logistic regression highlights the association between adolescent hazardous alcohol consumption and hazardous drinking by the father. Furthermore either parent permitting their adolescent to drink alcohol on special occasions was associated with hazardous alcohol consumption in the adolescent. Conclusion: The findings of this research notes a liberal attitude to alcohol and increased levels of consumption by the parent are linked to hazardous adolescent drinking behaviour. Future action plans aimed at combatting adolescent hazardous alcohol consumption should also be aimed at tackling parents’ attitudes towards and consumption of alcohol.

Structure et évolution du pergélisol depuis le Pléistocène Tardif, Beaver Creek, Yukon

Le site routier expérimental de Beaver Creek (62º 20’ 20’’ N – 140º 50’ 10’’ O) est sis sur la moraine de Beaver Creek pré datant le Dernier Maximum Glaciaire. Dans un périmètre d’un kilomètre carré, son relief, sa végétation, son sol et sa cryostratigraphie ont été étudiés avec une perspective géosystémique, afin d’en détailler la catena et sa structure. Ensuite, la cryostratigraphie a été interprétée pour suggérer un modèle d’évolution du paysage. Enfin, les changements récents y ont été intégrés en vue d’actualiser la tendance évolutive du géosystème. Il ressort de cet ouvrage que la durabilité du pergélisol est fortement appuyée par la présence des milieux humides dans les replats. Quelques affleurements de la moraine sont toujours visibles, quoique faiblement exprimés. Ils contiennent peu de glace et leur teneur en matière organique est mince. Quant aux dépressions, elles sont peu profondes et étendues. Non seulement elles ont hérité des sédiments érodés des crêtes, mais elles ont aussi fixé une quantité importante de glace et de matière organique par le truchement d’un pergélisol syngénétique (>15 m) généré par le climat et protégé par l’écosystème. Au moins un évènement de thermo-érosion est survenu avant le dernier stade d’aggradation syngénétique (Holocène), mais il n’a été que partiel. L’actuel réchauffement climatique menace d’engager un autre épisode de dégradation à l’échelle du bassin versant. Contrairement au changement climatique, l’utilisation du territoire provoque déjà la dégradation du pergélisol, mais de manière localisée seulement.