Hierarchical Linear Modeling Research Papers (original) (raw)

This thesis consists of three empirical studies in economics of education on the determinants and consequences of language-in-education (LiE) policies. The “Environmental settings – Inputs – Processes – Immediate outcomes – Long-term... more

This thesis consists of three empirical studies in economics of education on the determinants and consequences of language-in-education (LiE) policies. The “Environmental settings – Inputs – Processes – Immediate outcomes – Long-term outcomes” (EIPOL) evaluation model is applied to LiE policies and programs and serves as the overall framework of this research (see Introductory Chapter). Each study then targets at least one stage of the EIPOL framework to test the validity of the “green” vs. “free-market” linguistic theories. Whereas the two first studies derive models tested empirically in the African context, the third is tested on a sample of countries from the International Adult Literacy Survey (IALS). The first study, Rationales to Language-in-Education Policies in Postcolonial Africa: Towards a Holistic Approach, considers two issues. First, it explores the factors affecting the choice of an LiE policy in 35 African countries. The results show that the countries adopting a uni...

The assignment – selection problem used to find one-to- one match of given “Users” to “Laptops”, the main objective is to minimize the cost as per user requirement. This paper presents satisfactory solution for real assignment – Laptop... more

The assignment – selection problem used to find one-to- one match of given “Users” to “Laptops”, the main objective is to minimize the cost as per user requirement. This paper presents satisfactory solution for real assignment – Laptop selection problem using MATLAB coding.

Providing undocumented immigrants access to public education remains a pertinent issue facing both institutions of higher education and state governments. While instate resident tuition (ISRT) has remained a contentious policy, little is... more

Providing undocumented immigrants access to public education remains a pertinent issue facing both institutions of higher education and state governments. While instate resident tuition (ISRT) has remained a contentious policy, little is known about how such policies, as well as other state contexts, influence college students’ attitudes toward unauthorized immigrant students’ educational access. Using three-level multilevel models, we sought to understand how political, economic, and demographic contexts at the institutional and state level affect the development of US citizen students’ views toward undocumented immigrants’ access to public education during their undergraduate years. After controlling for student-level effects, findings show that institutional variables such as selectivity, control, and percentage of low-income students enrolled contribute to students’ attitude development. At the state level, findings show that students who attend institutions within states that have ISRT policies have more positive views towards undocumented immigrants’ access to public education at the end of college. This research highlights the critical need for higher education researchers, institutional leaders, and policy makers to better understand how institutional and state contexts shape students’ understanding of larger sociopolitical issues.

Recent studies suggest that habitat amount is the main determinant of species richness, whereas habitat fragmentation has weak and mostly positive effects. Here, we challenge these ideas using a multi-taxa database including 2230... more

Recent studies suggest that habitat amount is the main determinant of species richness, whereas habitat fragmentation has weak and mostly positive effects. Here, we challenge these ideas using a multi-taxa database including 2230 estimates of forest-dependent species richness from 1097 sampling sites across the Brazilian Atlantic Forest biodiversity hotspot. We used a structural equation modeling approach, accounting not only for direct effects of habitat loss, but also for its indirect effects (via habitat fragmentation), on the richness of forest-dependent species. We reveal that in addition to the effects of habitat loss, habitat fragmentation has negative impacts on animal species richness at intermediate (30–60%) levels of habitat amount, and on richness of plants at high (>60%) levels of habitat amount, both of which are mediated by edge effects. Based on these results, we argue that dismissing habitat fragmentation as a powerful force driving species extinction in tropical forest landscapes is premature and unsafe

New Hampshire’s Performance Assessment of Competency Education (PACE) pilot received a waiver from federal statutory requirements related to state annual achievement testing starting in the 2014-15 school year. PACE is considered an... more

New Hampshire’s Performance Assessment of Competency Education (PACE) pilot received a waiver from federal statutory requirements related to state annual achievement testing starting in the 2014-15 school year. PACE is considered an “innovative” assessment and
accountability system because performance assessments are used to help determine student proficiency in most federally required grades and subjects instead of the state achievement test. One key criterion for success in the early years of the PACE innovative assessment system is “no harm” on the statewide accountability test. This descriptive study examines the effect of PACE on Grades 8 and 11 mathematics and English language arts student achievement during the first three years of
implementation (2014-15, 2015-16, and 2016-17 school years) and the extent to which those effects vary for certain student subgroups using results from the state’s accountability tests (Smarter
Balanced and SATs). Findings suggest that students in PACE schools tend to exhibit small positive effects on the Grades 8 and 11 state achievement tests in both subjects in comparison to students
attending non-PACE comparison schools. Lower achieving students tended to exhibit small positive differential effects, whereas male students tended to exhibit small negative differential effects.
Implications for research, policy, and practice are discussed.

Research in Artificial Intelligence has been a forerunner in developing the most detailed and formalized theories that create consistent abstraction hierarchies for planning and problem solving. However, the representational methods to... more

Research in Artificial Intelligence has been a forerunner in developing the most detailed and formalized theories that create consistent abstraction hierarchies for planning and problem solving. However, the representational methods to exploit these theories are complicated, which limit their application into many disciplines, specifically engineering. The objective of this paper is threefold: to simplify the representation of current AI-based planning, to identify the properties that ensure effective development of abstraction hierarchies, and accordingly, to develop a methodology for effective and consistent generation of abstraction hierarchies. The proposed methodology achieves these objectives by integrating the well-established AI hierarchical abstraction theories with Steward’s practical Design Structure Matrices (DSM). The effectiveness of the developed methodology is demonstrated by applying it to the conceptual design on a facility layout of manufacturing plant that produces high voltage power cables.

This study aims to investigate the mediating effect of academic procrastination on the relationship between social media addiction and academic success. The study employed the multi-factorial predictive correlational model, and the study... more

This study aims to investigate the mediating effect of academic procrastination on the relationship between social media addiction and academic success. The study employed the multi-factorial predictive correlational model, and the study group consisted of 184 pre-service social studies teachers attending a public university in the south of Turkey in the 2019-2020 academic year. The data were collected by means of the “Social Media Addiction Scale for Adolescents” and the “Tuckman Procrastination Scale.” For academic success, participants’ grade point averages were considered. Descriptive statistics, correlations, hierarchical regression analysis, and mediation analysis proposed by Hayes (2018) were used for data analysis. Correlation analysis results revealed that social media addiction is positively correlated with academic procrastination and negatively correlated with academic success. Also, a negative correlation was found between academic procrastination and academic success. According to hierarchical regression analysis results, social media addiction positively predicted academic procrastination and negatively predicted academic success. Also, academic procrastination negatively predicted academic success. Finally, according to the results of the mediation analysis, the partial mediating effect of academic procrastination in the relationship between social media addiction and academic success was statistically significant. Besides, social media addiction and academic procrastination significantly explained 43% of the variance in academic success. The results are discussed in the context of the effects of social media addiction on academic responsibility and academic performance.
Keywords: Social media addiction, academic procrastination, pre-service social studies teachers’ hierarchical regression analysis, mediation analysis

In recent years, partial least square structural equation modeling has been enjoyed popularly since the various package for partial least square established. Besides, this method can be known as the the next second generation modeling or... more

In recent years, partial least square structural equation modeling has been enjoyed popularly since the various package for partial least square established. Besides, this method can be known as the the next second generation modeling or soft modeling that can be a great helpful among the researchers and practitioners to accomplish their objective research. In this paper also intend to modeling the second higher order construct (Hierachical Component) as the advance in partial least structural equation modeling (PLS-SEM) using smartpls which is the newest package. In this application of this method, we can create a higher order construct, in particular, the reseracher should empahsize for many aspect in order to ensure this model is more relevance and significant. Thus, the application using reflective-formative should be carry out in order to obtain the best model. In some instance, the author present the guideline to conduct this analysis with a real example so that the researchers outside will be more understanding and enjoyed for this new application.

The aim of this paper is to assess the expectations of hotel guests in relation to the services offered by the hotel. For the purpose of this research, data on 6,768 hotels located in 47 capital cities in Europe were collected from the... more

The aim of this paper is to assess the expectations of hotel guests in relation to the services offered by the hotel. For the purpose of this research, data on 6,768 hotels located in 47 capital cities in Europe were collected from the website www.booking.com. We have used all information available on the website regarding the hotels chosen on the basis of previously specified criteria, including ratings given by the registered users. The methods of partial correlation and hierarchical regression analysis were then conducted. Research results indicate that the number of stars is the most important factor that influences overall customer satisfaction in the hotel industry. We find that room price, the presence of air-conditioning in rooms, lobby bar, and free Wi-Fi are variables that positively correlate with customer satisfaction, whereas the number of rooms in hotel and distance from the city center are negatively correlated with customer satisfaction.

Reporting effect sizes in scientific articles is increasingly widespread and encouraged by journals; however, choosing an effect size for analyses such as mixed-effects regression modeling and hierarchical linear modeling can be... more

Reporting effect sizes in scientific articles is increasingly widespread and encouraged by journals; however, choosing an effect size for analyses such as mixed-effects regression modeling and hierarchical linear modeling can be difficult. One relatively uncommon, but very informative, standardized measure of effect size is Cohen’s f2, which allows an evaluation of local effect size, i.e., one variable’s effect size within the context of a multivariate regression model. Unfortunately, this measure is often not readily accessible from commonly used software for repeated-measures or hierarchical data analysis. In this guide, we illustrate how to extract Cohen’s f2 for two variables within a mixed-effects regression model using PROC MIXED in SAS® software. Two examples of calculating Cohen’s f2 for different research questions are shown, using data from a longitudinal cohort study of smoking development in adolescents. This tutorial is designed to facilitate the calculation and reporting of effect sizes for single variables within mixed-effects multiple regression models, and is relevant for analyses of repeated-measures or hierarchical/multilevel data that are common in experimental psychology, observational research, and clinical or intervention studies.

Öz OECD'nin PISA 2012 Türkiye problem çözme raporuna göre Türkiye ve Sırbistan aynı matematik okuryazarlık düzeyindedir. Fakat Sırbistan'ın ortalama problem çözme yeterliğinin, Türkiye'den daha yüksek olduğu ifade edilmiştir. Bu... more

Öz OECD'nin PISA 2012 Türkiye problem çözme raporuna göre Türkiye ve Sırbistan aynı matematik okuryazarlık düzeyindedir. Fakat Sırbistan'ın ortalama problem çözme yeterliğinin, Türkiye'den daha yüksek olduğu ifade edilmiştir. Bu doğrultuda bu çalışmada iki ülkenin problem çözme okuryazarlığına etki eden okul değişkenleri belirlenip karşılaştırılmıştır. Nedensel karşılaştırma yöntemi ile yürütülen bu çalışmada Türkiye örnekleminde 147 okuldan 4494 öğrenciye, Sırbistan örnekleminde ise 132 okuldan 4059 öğrenciye ait veri üzerinde ayrı ayrı HLM analizi yapılmıştır. HLM analizi sonucunda, Sırbistan için "engel ve aile bağışı" değişken etkileri, Türkiye için ise "terk, öğretmen morali ve matematik yarışı" değişken etkileri istatistiksel olarak anlamlı bulunmuştur. İki ülkede farklı değişkenlerin problem çözme okuryazarlığı üzerinde manidar etkileri olduğu görülse de bu değişkenlerin okul iklimi kavramının birer bileşeni olması oldukça dikkate değerdir. Anahtar Kelimeler: PISA 2012, problem çözme yeterliği, Türkiye, Sırbistan. Abstract According to the OECD's PISA 2012 Turkey problem-solving report, Turkey and Serbia are at the same mathematical literacy level. However, Serbia's average of problem-solving competency is said to be higher than Turkey's. In this study, school variables that affect problem-solving competency of the two countries were examined and compared. The method of the study was causal comparison method, and HLM analysis was performed on data of 4494 students from 147 schools in Turkey sample and 4059 students from 132 schools in Serbia sample separately. As a result of HLM analysis, "obstacle and family donation" variable for Serbia and "abandon, teacher morale and mathematics competition" variable for Turkey were statistically significant. Although it was found that for each countries different variables influence the problem-solving competency, it was quite remarkable that these variables are in common in that they are components of the school climate concept. GİRİŞ Çok fazla değişkenin etkisinde sürekli değişen ve gelişen dünyada, toplumlar arası etkileşim kaçınılmaz hale gelmiştir. Bu durum, sınırların ortadan kalkmasına ve hiçbir toplumun ve ulusun, dış dünyadan bağımsız olarak kendi içerisinde kapalı kalamamasına neden olmuştur. Bu karmaşık ve rekabetin en üst düzeye çıktığı ortamlarda sağlanacak başarı, öncelikle nitelikli insan gücüne bağlıdır. Bu bağlamda eğitim, küresel dönemin dinamikleri doğrultusunda çok boyutlu ve çok yönlü nitelikli insan modelinin yetiştirilmesinde, en etkin ve önemli araçlardan biridir (Demir, 2010:1-5).

Humanity is on the threshold of recognizing the fundamental error in its view of life and death. Both death as well as active life is necessary to the vital formation of a larger, more essential whole. In this paper, I apply the sociology... more

Humanity is on the threshold of recognizing the fundamental error in its view of life and death. Both death as well as active life is necessary to the vital formation of a larger, more essential whole. In this paper, I apply the sociology of knowledge and change as it pertains to death and focus on ways in which we can step outside its traditional frameworks and limitations. I also discuss topics related to death such as birth, aging, sickness, and war, and examine cultural differences in attitudes toward death. I offer varying perspectives including the Buddhist view and from these draw implications and conclusions. I apply the lenses of contemporary social scientists such as Edgar Morin, Kenneth Gergen, Edward Stewart, Milton Bennett, Mary Catherine Bateson, E. Doyle McCarthy, Philip Slater, and Piotr Sztompka. To these I add other relevant passages from the writings and speeches of key thinkers on the topic of death, in particular, Buddhist philosopher, peacebuilder, and educator, Daisaku Ikeda. To construct a more humanistic and sustainable view of life, it is first of all crucial to establish a culture which perceives death in its larger living context as but one cycle in the expansive eternity of life.

Regarding the methods used to examine the early maternal age-child academic outcomes relationship, the extant literature has tended to examine change using statistical analyses that fail to appreciate that individuals vary in their rates... more

Regarding the methods used to examine the early maternal age-child academic outcomes relationship, the extant literature has tended to examine change using statistical analyses that fail to appreciate that individuals vary in their rates of growth. Of the one study I have been able to find that employs a true growth model to estimate this relationship, the authors only controlled for characteristics of the maternal household after family formation;
confounding background factors of mothers that might select them into early childbearing, a possible source of bias, were ignored. The authors’ findings nonetheless suggested an inverse relationship between early maternal age, i.e., a first birth between
the ages of 13 and 17, and Canadian adolescents’ mean math performance at age 10. Early maternal age was not related to the linear slope of age. To elucidate whether the early maternal age-child academic outcomes association, treated in a growth context, is consistent with this finding, the present study built on it using US data and explored children’s mathematics and reading trajectories from age 5 on. Its unique contribution is that it further
explicitly controlled for maternal background factors and employed a three-level growth model with repeated measures of children nested within their mothers. Though the strength of the relationship varied between mean initial academic performance and mean academic growth, results confirmed that early maternal age was negatively related to children’s mathematics and reading achievement, net of post-teen first birth child-specific and maternal household factors. Once maternal background factors were included, there was no statistically significant relationship between early maternal age and either children’s mean initial mathematics and reading scores or their mean mathematics and
reading growth.

Much scholarly literature has investigated the connection of narcissism and Internet use, specifically focused on online social networks. However, there is no consensus about how the narcissists’ Internet use impacts their social... more

Much scholarly literature has investigated the connection of narcissism and Internet use, specifically focused on online social networks. However, there is no consensus about how the narcissists’ Internet use impacts their social relations. In part, mixed findings might be explained by failure to account for two distinct types of narcissism, namely a grandiose type and a vulnerable type. In the present study, we expected these two facets of narcissism to show different patterns of associations with Internet behaviors and social outcomes. Anonymous, self-report data were collected from N = 532 late adolescent/young adult participants (mean age = 23.33, 54.9% female). Findings from SEM analyses showed that the links between narcissism and social anxiety/social self-efficacy were partially mediated by preference for online social interactions (POSI); however, the two types of narcissism show distinct links to the two outcomes. Vulnerable narcissism was positively associated with POSI, which indirectly predicted problems for both measures of social relations; in contrast, grandiose narcissism was only directly and positively associated with social self-efficacy and negatively with social anxiety.

Examines the sense of community (SOC) within neighborhoods and the dimensions of social capital (SC). We have four main goals for this chapter. One is to inform researchers and program planners in community development, urban policy, and... more

Examines the sense of community (SOC) within neighborhoods and the dimensions of social capital (SC). We have four main goals for this chapter. One is to inform researchers and program planners in community development, urban policy, and social services that many concepts thoroughly studied by community psychologists (sense of community, collective efficacy/empowerment, citizen participation, neighboring) are part of SC. Our second goal is to introduce more community psychologists to SC. Third, to both audiences, we expect to show that residential neighborhood SOC is at least as strongly related to other SC dimensions as are demographics and other widely studied community-focused cognitions (place attachment, community satisfaction, community confidence, and communitarianism--or community values). In addition to those interdisciplinary aims, our fourth goal is to explore SOC and its relationships to SC using multi-level analysis. The relationship between SOC and SC--whether they operate together, separately, or nested one within the other--and on what level(s) they operate are critical to our understanding of both concepts.

We propose a Hierarchical Decision Support System (HDSS) for production planning which enables production planners to utilize complex and structured planning algorithms interactively with no difficulty. The suggested system represents a... more

We propose a Hierarchical Decision Support System (HDSS) for production planning which enables production planners to utilize complex and structured planning algorithms interactively with no difficulty. The suggested system represents a higher level planning tool than MRP: namely, it encompasses aggregate planning, family and end item planning levels. The HDSS is integrated with MRP through the Master Production Schedule (at the end item level) which is transferred to MRP. The feasibility at all planning levels is preserved through database manipulations which enable communication among different planning hierarchies. The key features of the proposed system are the ease of data manipulation and the highly interactive nature of the system provided by the user-interface. The dialogue management system hides the theoretical background of the model base consisting of multi-optional aggregate planning models and disaggregation algorithms used at the family and end item planning levels.

Caesalpinia bonduc L. is an important medicinal plant threatened by overexploitation. In the present study, the impact of climate on seed morphology, germination capacity, seedling, and plant growth of C. bonduc were evaluated. A total of... more

Caesalpinia bonduc L. is an important medicinal plant threatened by overexploitation. In the present study, the impact of climate on seed morphology, germination capacity, seedling, and plant growth of C. bonduc were evaluated. A total of 2000 seeds were collected in Sudanian and Guinean climate zones of Africa and their length, width, thickness, weight and color were recorded. A hierarchical classification and canonical discriminant analysis were applied to the above traits of seeds from the different climatic zones. An analysis of variance with repeated measures was applied to seeds morphotypes identified by the hierarchical classification to test for the effect of these morphotypes on seed germination, seedling and plant growth. Hierarchical classification helped to identify four seed morphotypes. Canonical discriminant analysis performed on these morphotypes revealed highly significant differences. Morphotypes 1 and 3 comprised green seeds mainly from the Sudanian zone while morphotypes 2 and 4 gathered grey seeds mainly from Guinean zone. Morphotype 3 had the longest seeds while the shortest seeds were from morphotype 1. The heaviest seeds were found in morphotype 4 whereas the lightest ones were from morphotype 1. Seeds of morphotype 4 were the thickest and widest, while the slimmest and most narrow ones were grouped in morphotype 1. Morphotype 3, consisting of large green seeds mainly from Sudanian zone, was superior in terms of seedling and plant growth among all morphotypes and should be the best choice for planting purposes of the species.

In this study, it is aimed to examine the effect of classroom assessment on science and mathematics achievements. For this purpose, hierarchical linear modeling (HLM) is performed using variables of like learning science/maths, engage... more

In this study, it is aimed to examine the effect of classroom assessment on science and mathematics achievements. For this purpose, hierarchical linear modeling (HLM) is performed using variables of like learning science/maths, engage teaching in science/maths, confidence in science/ maths, and home resources for learning variables at the student level, and experience, education level, homework, and assessment at the teacher level. The sample of the study consists of 4th grade students who participated in TIMSS 2015 in Turkey. According to the findings; 36% of variance in science achievement, and 40% of variance in mathematics achievement are due to variability between classes. In a random coefficient model, all student variables were found to be statistically significant predictors of science and mathematics achievement. Among these variables, the greatest effect size is self-confidence variability. Only the teacher variables are added according to the Means as the outcome model; the teacher's experience and emphasis to national achievement tests of monitoring students' progress had a statistically significant effect on science and mathematics achievement. Finally, according to the intercept and slopes of the outcomes model, the most important variable is the emphasis to national achievement tests of monitoring students' progress in both science and mathematics.

For longitudinal surveys, there is little discussion on how call record data are able to account for household nonresponse. This paper uses call records as well as observed data from Understanding Society’s Wave 1 to model Wave 2, Wave 3... more

For longitudinal surveys, there is little discussion on how call record data are able to account for household nonresponse. This paper uses call records as well as observed data from Understanding Society’s Wave 1 to model Wave 2, Wave 3 and Wave 4 household contact and cooperation propensities. Multi level logistic models are used to account for the nested structure of the data (households within interviewers). Results indicate that households which repeated unproductive contacts, broke appointments, registered above median proportion of "no replies", or began the call sequence with an unproductive contact in Wave 1 are at risk of future nonresponse.

Esta investigación provee evidencia acerca del efecto del acceso a cobertura de telefonía móvil sobre la mejora de los recursos financieros, materiales y sociales de los hogares de la sierra rural del Perú durante el período 2009 – 2016,... more

Esta investigación provee evidencia acerca del efecto del acceso a cobertura de telefonía móvil sobre la mejora de los recursos financieros, materiales y sociales de los hogares de la sierra rural del Perú durante el período 2009 – 2016, el cual cubre la mayor parte de la fase de máxima expansión e innovación de las telecomunicaciones en el país. Asimismo, explora el efecto diferenciado de la cobertura móvil sobre los recursos financieros / ingresos según si provienen de actividades agropecuarias o no agropecuarias; así como los posibles efectos heterogéneos de acceder a cobertura móvil bajo distintas configuraciones y duración de la exposición al tratamiento. Para ello, se empleó un Modelo Lineal
Multinivel (MLM) que consideró los diferentes niveles de especificación de las variables que modelan la relación entre el acceso a cobertura de telefonía móvil y los distintos tipos de recursos de los hogares, y se usó como marco de análisis el Enfoque de la Elección. Los principales hallazgos del estudio muestran que el acceso a cobertura móvil mejoró los recursos financieros de los hogares de la sierra rural pero solo mediante el canal de mejora de los ingresos no agropecuarios, registrándose un efecto negativo significativo sobre los ingresos agropecuarios no salariales. Asimismo, se identificó que el acceso a cobertura móvil aumentó significativamente la probabilidad de que los hogares mejoren sus recursos materiales pero redujo la probabilidad de que incrementen sus recursos sociales. Por último, se encontró que un acceso prologado al tratamiento intensificó los efectos positivos encontrados sobre los recursos financieros y materiales de los hogares.

Machine learning algorithms were broadly classified into supervised, unsupervised and semi-supervised learning algorithms. Supervised learning algorithms were classified into classification and regression techniques whereas unsupervised... more

Machine learning algorithms were broadly classified into supervised, unsupervised and semi-supervised learning algorithms. Supervised learning algorithms were classified into classification and regression techniques whereas unsupervised learning algorithms were classified into clustering and dimensionality reduction. This paper deals with the evaluation of clustering techniques under unsupervised learning. Clustering is the process of coordinating the data of similar properties under single group. There are several clustering techniques available such as partitional clustering, hierarchical clustering, Fuzzy clustering, Density-based clustering, and Model-based clustering. This paper focuses on the analysis and evaluation of K-means clustering of partitional method and Divisive clustering of hierarchical method. The result of evaluation shows that K-means clustering can hold better for large datasets and it also takes less time than hierarchical clustering.

We had three aims in the present study: (1) to examine the dimensionality of various evaluative approaches to scoring writing samples (e.g., quality, productivity, and curriculum based writing [CBM]) , (2) to investigate unique language... more

We had three aims in the present study: (1) to examine the dimensionality of various evaluative approaches to scoring writing samples (e.g., quality, productivity, and curriculum based writing [CBM]) , (2) to investigate unique language and cognitive predictors of the identified dimensions, and (3) to examine gender gap in the identified dimensions of writing. These questions were addressed using data from second and third grade students (N = 494). Data were analyzed using confirmatory factor analysis and multilevel modeling. Results showed that writing quality, productivity, and CBM scoring were dissociable constructs, but that writing quality and CBM scoring were highly related (r = .82). Language and cognitive predictors differed among the writing outcomes. Boys had lower writing scores than girls even after accounting for language, reading, attention, spelling, handwriting automaticity, and rapid automatized naming. Results are discussed in light of writing evaluation and a deve...

Recent research has commonly used hierarchical linear models (HLMs). Also known as multilevel models, HLMs can be used to analyze a variety of questions with either categorical or continuous dependent variables. With hierarchical linear... more

Recent research has commonly used hierarchical linear
models (HLMs). Also known as multilevel models, HLMs can be used to
analyze a variety of questions with either categorical or continuous
dependent variables. With hierarchical linear models, each level (e.g.,
student, classroom, and school) is formally represented by its own submodel.
This study presents detailed descriptions of practical procedures to
conduct nested data analysis using HLM.