Using Hierarchical Linear Modeling to Examine How Individual SLPs Differentially Contribute to Children's Language and Literacy Gains in Public Schools

Purpose The purpose of this study was twofold: (a) to determine the unique contributions in children's language and literacy gains, over 1 academic year, that are attributable to the individual speech-language pathologist (SLP) and (b) to explore possible child- and SLP-level factors that may further explain SLPs' contributions to children's language and literacy gains. Method Participants were 288 kindergarten and 1st-grade children with language impairment who were currently receiving school-based language intervention from SLPs. Using hierarchical linear modeling, we partitioned the variance in children's gains in language (i.e., grammar, vocabulary) and literacy (i.e., word decoding) that could be attributed to their individual SLP. Results Results revealed a significant contribution of individual SLPs to children's gains in grammar, vocabulary, and word decoding. Children's fall language scores and grade were significant predictors of SLPs' contributions, although no SLP-level predictors were significant. Conclusions The present study makes a first step toward incorporating implementation science and suggests that, for children receiving school-based language intervention, variance in child language and literacy gains in an academic year is at least partially attributable to SLPs. Continued work in this area should examine the possible SLP-level characteristics that may further explicate the relative contributions of SLPs.

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Children's Active Engagement in Public School Language Therapy Relates to Greater Gains

American Journal of Speech-Language Pathology ◽

10.1044/2020_ajslp-19-00157 ◽

2020 ◽

Vol 29 (3) ◽

pp. 1505-1513

Author(s):

Mary Beth Schmitt

Keyword(s):

Public Schools ◽

Hierarchical Linear Modeling ◽

Language Impairment ◽

Active Engagement ◽

Linear Modeling ◽

Language Therapy ◽

Significant Component ◽

Usual Therapy ◽

Business As Usual ◽

Therapy Sessions

Purpose The current study examined children's engagement as an active ingredient of language therapy in public schools and considered the potential interplay between engagement and dose on outcomes. Method Participants included 135 children with language impairment receiving business-as-usual therapy from 70 speech-language pathologists. Two videotaped therapy sessions from each participating child were coded for children's level of engagement and time in language-focused therapy (dose). Results Hierarchical linear modeling was used for analyses; children's level of engagement (i.e., active engagement) was significantly, positively related to children's language gain and was not moderated by dose. Conclusion Findings suggest that children's active participation in therapy sessions is a significant component to effective language therapy and underscores the need for further research.

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The Frequency and Nature of Communication Between School-Based Speech-Language Pathologists and Caregivers of Children With Language Impairment

American Journal of Speech-Language Pathology ◽

10.1044/2017_ajslp-16-0235 ◽

2017 ◽

Vol 26 (4) ◽

pp. 1193-1201 ◽

Cited By ~ 1

Author(s):

Sherine R. Tambyraja ◽

Mary Beth Schmitt ◽

Laura M. Justice

Keyword(s):

Socioeconomic Status ◽

Early Literacy ◽

Language Impairment ◽

Work Experience ◽

Work Conditions ◽

Language And Literacy ◽

Speech Language Pathologists ◽

School Based ◽

Communication Frequency ◽

Academic Year

PurposeThe present study investigates the extent to which school-based speech-language pathologists (SLPs) communicate with the caregivers of children with language impairment and the factors that are significantly associated with frequent communication. In addition, this study investigates the extent to which frequent SLP–caregiver communication is associated with change in language and literacy abilities of children.MethodTo address the study aims, weekly communication logs from 73 SLPs, serving 3–5 children with language impairment in grades K-2, were collected for a complete academic year. Logs detailed the frequency and nature of SLP–caregiver communication. Information regarding children's age, language ability, and socioeconomic status were gathered at study onset; additionally, SLPs completed a questionnaire about their work experience and current work conditions (e.g., caseload size and job satisfaction). Finally, children were administered grammar, vocabulary, and early literacy assessments at the beginning and end of the academic year.ResultsDescriptive results indicate that (a) the most common type of communication was via homework, (b) children's socioeconomic status was related to communication frequency, and (c) increased SLP–caregiver communication related to increased grammar gains over the academic year.ConclusionThese results suggest that SLP–caregiver communication may be important for children's language outcomes; further studies exploring ways to support these communicative efforts are warranted.

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Factors Determining Income among Real Estate Salespersons: The Impacts of Individual Conditions, Franchises, and Regular Chains

International Journal of Economics and Finance ◽

10.5539/ijef.v7n11p94 ◽

2015 ◽

Vol 7 (11) ◽

pp. 94

Author(s):

Chun-Chang Lee ◽

Cheng-Huang Tung ◽

Yu-Heng Lee ◽

Shu-Man You

Keyword(s):

Real Estate ◽

Hierarchical Linear Modeling ◽

Positive Impact ◽

Working Hours ◽

Education Level ◽

Linear Modeling ◽

Individual Level ◽

The Individual ◽

The Given ◽

Regular Chains

<p>This study explores the factors that affect the incomes of real estate salespersons by applying hierarchical linear modeling (HLM) to investigate the incomes of real estate salespersons in Kaohsiung. A total of 510 questionnaires were distributed to large chain housing agencies, of which a total of 319 effective samples were retrieved from 54 branch stores, for an effective return rate of 62.55%. The empirical results showed that individual incomes vary significantly from store to store. About 4.8% of the variation in individual incomes was due to differences among different branch stores. The individual income of a real estate salesperson is also significantly affected by individual-level factors such as age, working hours, and working experience. The marginal impact of education level, age, working hours, and working experience on real estate salesperson income is moderated by the type of store at which the given salesperson works. In addition, a branch store’s location has a direct, significant, and positive impact on a real estate salesperson’s income.</p>

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Hypothesized, Directly-Coded Curve Shapes in Growth Curve Analysis: An Example

Journal of Methods and Measurement in the Social Sciences ◽

10.2458/v3i2.16476 ◽

2013 ◽

Vol 3 (2) ◽

pp. 13 ◽

Cited By ~ 1

Author(s):

Patricia M. Herman ◽

Lee Sechrest

Keyword(s):

Hierarchical Linear Modeling ◽

Growth Curve ◽

Degrees Of Freedom ◽

Growth Curves ◽

Curve Analysis ◽

Small Samples ◽

Growth Curve Analysis ◽

Linear Modeling ◽

Individual Level ◽

The Individual

Growth curve analysis provides important informational benefits regarding intervention outcomes over time. Rarely, however, should outcome trajectories be assumed to be linear. Instead, both the shape and the slope of the growth curve can be estimated. Non-linear growth curves are usually modeled by including either higher-order time variables or orthogonal polynomial contrast codes. Each has limitations (multicollinearity with the first, a lack of coefficient interpretability with the second, and a loss of degrees of freedom with both) and neither encourages direct testing of alternative hypothesized curve shapes. Especially in studies with relatively small samples it is likely to be useful to preserve as much information as possible at the individual level. This article presents a step-by-step example of the use and testing of hypothesized curve shapes in the estimation of growth curves using hierarchical linear modeling for a small intervention study. DOI:10.2458/azu_jmmss_v3i2_herman

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First Impressions, Team Satisfaction and Work-Related Flow: A Multilevel Analysis

Proceedings of the Human Factors and Ergonomics Society Annual Meeting ◽

10.1177/1541931218621177 ◽

2018 ◽

Vol 62 (1) ◽

pp. 782-786

Author(s):

Sarah Berger ◽

Jeffery Hanrahan ◽

Andrea Bizarro ◽

Robert Henning

Keyword(s):

Hierarchical Linear Modeling ◽

Ad Hoc ◽

First Impressions ◽

Linear Modeling ◽

Team Members ◽

Work Related ◽

Team Satisfaction ◽

The Individual ◽

Ad Hoc Teams ◽

Flow Experiences

First impressions of fellow team members, as well as individual satisfaction with one’s team, are each related to work-related flow experiences but they are rarely studied in combination. To address this gap we collected measures of all three in a laboratory study of dyadic teams (N=55). First impressions were assessed prior to the start of a management simulation task, and both team satisfaction and work-related flow were assessed afterwards. Hierarchical linear modeling revealed that measures of team satisfaction at both the individual and team levels were predictive of work-related flow experiences; an interaction between the discrepancy in first impression ratings within each team and individual ratings of team satisfaction was also found. Findings suggest that discrepancies in first impressions interact with team satisfaction in ways that may negatively impact work-related flow experiences, which in turn has the potential to impair team formation and performance effectiveness of ad hoc teams.

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The Challenge of Holistic Student Support: Investigating Urban Adolescents’ Constructions of Support in the Context of School

Harvard Educational Review ◽

10.17763/haer.84.3.prx141q550r3808p ◽

2014 ◽

Vol 84 (3) ◽

pp. 314-340 ◽

Cited By ~ 2

Author(s):

Gretchen Brion-Meisels

Keyword(s):

Public Schools ◽

Urban Adolescents ◽

Student Support ◽

Cultural Narratives ◽

Support Providers ◽

School Based ◽

Group Data ◽

Focus Group Data ◽

The Individual ◽

Permanent Structure

In this piece, Gretchen Brion-Meisels investigates how adolescents conceptualize support in the context of school. Student support systems have become a permanent structure in most U.S. public schools, responsible for ensuring equal access to support services. Unfortunately, little is known about how adolescents make meaning of school-based support. To answer this question, Brion-Meisels explores how urban adolescents in a northeastern city talk about support, paying close attention to the cultural narratives that underlie their conceptions. Analyzing text from survey, interview, and focus group data, she argues that adolescents in the sample both draw on and actively resist dominant societal discourses of support. Findings suggest that support providers would benefit from better understanding the cultural and contextual narratives underlying youth conceptions of support, as well as the individual perspectives of the youth that they serve. In addition, Brion-Meisels contends that adults must shift their own discourses of support if they want to create spaces in which young people feel empowered and safe to seek help.

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Research on the Innovation Method of HRM Based on Information Technology

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.687-691.4485 ◽

2014 ◽

Vol 687-691 ◽

pp. 4485-4488

Author(s):

Man Jing Zhang

Keyword(s):

Firm Performance ◽

Hierarchical Linear Modeling ◽

Psychological Contract ◽

High Performance ◽

Affective Commitment ◽

Organizational Level ◽

Linear Modeling ◽

Individual Level ◽

Relational Contract ◽

The Individual

As an organization s strategy to manage the employment relationship, high-performance work system (HPWS) may lead to superior firm performance and favorable employee outcomes through cultivating the relational aspects of employee’s psychological contract. In this study, we investigated the processes (mediation and moderation) linking HPWS and outcomes at both the organizational and individual levels. Hierarchical linear modeling (HLM) analysis on a sample of 1129 employees from 92 firms in the Pearl River Delta of China indicated that HPWS was associated with increased firm performance and decreased turnover rate at the organizational level, and relational contract fully mediated the cross-level relationships between HPWS and employees affective commitment and in-role performance at the individual level. In addition, perceived supervisor support moderated the HPWS and relational contract relationship. We discuss theoretical and practical implications to end of this paper.

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General Slowing in Language Impairment

Journal of Speech Language and Hearing Research ◽

10.1044/1092-4388(2001/036) ◽

2001 ◽

Vol 44 (2) ◽

pp. 446-461 ◽

Cited By ~ 38

Author(s):

Jennifer Windsor ◽

Rochelle L. Milbrath ◽

Edward J. Carney ◽

Susan E. Rakowski

Keyword(s):

Word Recognition ◽

Hierarchical Linear Modeling ◽

Language Impairment ◽

Ordinary Least Squares ◽

Random Coefficients ◽

Least Squares Regression ◽

Linear Modeling ◽

Data Set ◽

Significant Difference ◽

General Slowing

Although the general slowing hypothesis of language impairment (LI) is well established, the conventional method to test the hypothesis is controversial. This paper compares the usual method, ordinary least squares regression (OLS), with another method, hierarchical linear modeling with random coefficients (HLM). The analyses used available response time (RT) data from studies of perceptual-motor, cognitive, and language skills of LI and chronological-age-matched (CA) groups. The data set included RT measures from 25 studies investigating 20 different tasks (e.g., auditory detection, mental rotation, and word recognition tasks). OLS and HLM analyses of the RT data yielded very different results. OLS supported general slowing for the LI groups, and indicated that they were significantly slower than CA groups across studies by an overall estimate of 10%. HLM indicated a larger average extent of LI slowing (18%). However, the variability around this average was much greater than that yielded by OLS, and the extent of slowing was not statistically significant. Importantly, HLM showed a significant difference in the RT relation between LI and CA groups across studies, indicating that study-specific slowing, rather than general slowing across studies, was present. A separate HLM analysis of two types of language tasks, picture naming and word recognition, was performed. Although the extent of slowing was equivalent across these tasks, the slowing was minimal (2%) and not significant. Methodological limitations of each analysis to assess general slowing are highlighted.

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Associations Between Daily Positive Communication and Sexual Desire and Satisfaction: A Comparison Between Traditional Analyses and Machine Learning

10.31234/osf.io/7wxv6 ◽

2021 ◽

Author(s):

Christine Leistner ◽

Laura Marika Vowels ◽

Matthew J Vowels ◽

Kristen Mark

Keyword(s):

Machine Learning ◽

Relationship Satisfaction ◽

Sexual Satisfaction ◽

Hierarchical Linear Modeling ◽

Sexual Desire ◽

Communication Strategies ◽

Linear Modeling ◽

Positive Communication ◽

The Individual ◽

Data Analytic

Communication is an important component of many healthy sexual and romantic relationships. Positive communication strategies including expressing fondness and affection, exchanging compliments, and disclosing information about oneself with a partner are associated with relationship and sexual satisfaction, but less is known about its association to sexual desire. Most of the current literature has used traditional statistical analyses that assume errors are normally distributed and that associations between variables are linear. Our study aimed to examine the ways daily levels of four positive communication strategies are associated with relationship satisfaction, sexual satisfaction, and sexual desire among 246 mixed sex couples (N = 492). We also compared traditional hierarchical linear modeling with machine learning to compare results from the different data analytic techniques. Findings indicated that daily positive communication received from a partner was associated with all outcome variables of interest that day for both partners in the couple. All positive communication strategies predicted daily levels of desire, sexual satisfaction, and relationship satisfaction for the individual and each had unique associations with partner outcomes. Unique nonlinear interactions were found using machine learning. Findings have implications for practitioners and provide insight into the differences in findings between traditional analyses and machine learning.

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