scholarly journals The Impact of Ignoring a Crossed Factor in Cross-Classified Multilevel Modeling

2021 ◽  
Vol 12 ◽  
Author(s):  
Soyoung Kim ◽  
Yoonhwa Jeong ◽  
Sehee Hong
Keyword(s):  
Random Effects ◽  
Hierarchical Linear Modeling ◽  
Fixed Effects ◽  
Random Effect ◽  
Information Criteria ◽  
Linear Modeling ◽  
Random Effect Modeling ◽  
Error Bias ◽  
The Impact ◽  
Level 2

The present study investigated estimate biases in cross-classified random effect modeling (CCREM) and hierarchical linear modeling (HLM) when ignoring a crossed factor in CCREM considering the impact of the feeder and the magnitude of coefficients. There were six simulation factors: the magnitude of coefficient, the correlation between the level 2 residuals, the number of groups, the average number of individuals sampled from each group, the intra-unit correlation coefficient, and the number of feeders. The targeted interests of the coefficients were four fixed effects and two random effects. The results showed that ignoring a crossed factor in cross-classified data causes a parameter bias for the random effects of level 2 predictors and a standard error bias for the fixed effects of intercepts, level 1 predictors, and level 2 predictors. Bayesian information criteria generally outperformed Akaike information criteria in detecting the correct model.

scholarly journals The Impact of Misspecified Random Effect Distribution in a Weibull Regression Mixed Model

Stats ◽  
2018 ◽  
Vol 1 (1) ◽  
pp. 48-76
Author(s):  
Freddy Hernández ◽  
Viviana Giampaoli
Keyword(s):  
Weibull Distribution ◽  
Random Effects ◽  
Mixed Models ◽  
Fixed Effects ◽  
Mixed Model ◽  
Random Effect ◽  
Estimation Procedure ◽  
Weibull Regression ◽  
Two Parameters ◽  
The Impact

Mixed models are useful tools for analyzing clustered and longitudinal data. These models assume that random effects are normally distributed. However, this may be unrealistic or restrictive when representing information of the data. Several papers have been published to quantify the impacts of misspecification of the shape of the random effects in mixed models. Notably, these studies primarily concentrated their efforts on models with response variables that have normal, logistic and Poisson distributions, and the results were not conclusive. As such, we investigated the misspecification of the shape of the random effects in a Weibull regression mixed model with random intercepts in the two parameters of the Weibull distribution. Through an extensive simulation study considering six random effect distributions and assuming normality for the random effects in the estimation procedure, we found an impact of misspecification on the estimations of the fixed effects associated with the second parameter σ of the Weibull distribution. Additionally, the variance components of the model were also affected by the misspecification.

scholarly journals Impact of Full IFRS, Accounting Standards for SMES and Company Demographics on Firms’ Return on Asset and Return on Equity using Panel Data Regression

2019 ◽  
Vol 8 (6S) ◽  
pp. 589-601 ◽  
Keyword(s):  
Least Squares ◽  
Random Effects ◽  
Fixed Effects ◽  
Random Effect ◽  
Ordinary Least Squares ◽  
Lagrangian Multiplier ◽  
Random Effects Model ◽  
Fixed Effects Model ◽  
Real Property ◽  
The Impact

Due to globalization, markets are becoming more interconnected as the companies are engaged in doing cross-border offerings. Currently, competitions are intensified because Domestic organizations discover themselves competing with each nearby opposite numbers and worldwide companies. But one component that hinders SMEs is the need for reliable and similar monetary data. According to Abarca (2014), adoption of a high-quality and consistent set of accounting requirements is critical so as for the businesses to remain competitive in ASEAN member states. This paper ambitions to answer the query, what modified into the extent of the impact of compliance with full IFRS and IFRS for SMEs on profitability of agencies belong to real property enterprise? This paper moreover sought to decide whether there may be a sizeable distinction among the groups’ compliance with the overall PFRS and the PFRS for SMEs and to determine whether or now not there is a massive distinction among the companies’ financial normal overall performance earlier than and after the adoption of the PFRS for SMEs.Paired T-test have become employed in case you need to determine whether there is a big distinction between the agencies’ compliance with the entire PFRS and the PFRS for SMEs and to decide whether or not there may be a big difference some of the groups’ monetary performance earlier than and after the adoption of the PFRS for SMEs. Using STATA, the great appropriate version for every economic ratio on the subject of degree of compliance emerge as determined on. First, take a look at parm command became used to find out which most of the Least Squares Dummy Variable Regression Modes (LSDV1, LSDV2, LSDV3) underneath the Fixed Effects Model is the ideal version. Afterwards, Hausman Fixed Random Test changed into used to pick out out which is more suitable amongst Fixed Effects Model and Random Effects Model. If Fixed Effects Model modified into the more appropriate one, the Wald’s test turn out to be used to determine the best version among Fixed Effects Model and Ordinary Least Squares Model. On the alternative hand, if Random Effects Model became the more suitable one, the Breusch and Pagan Lagrangian Multiplier Test for Random Effect have become used to decide the satisfactory version amongst Random Effects Model and Ordinary Least Squares. Moreover, if Ordinary Least Squares became the splendid model, it is going to be in addition tested to check for heteroscedasticity and multicollinearity. White’s test became used to check for heterescedasticity and Variance Inflation Factor have become used to test if multicollinearity is gift. The results display that the adoption of PFRS for SMEs stepped forward the compliance of Philippine real property SMEs. However, no vast alternate became said inside the financial average performance of those companies (as measured with the resource of cross back on assets and go back on equity). This was further supported by the results of the panel regression. This means that despite having a relatively

scholarly journals Analysis of lactation feed intakes for sows with extended lactation lengths

2017 ◽  
Vol 1 (1) ◽  
pp. 1-25
Author(s):  
F. A. Cabezón ◽  
A. P. Schinckel ◽  
Y. L. León ◽  
B. A. Craig
Keyword(s):  
Random Effects ◽  
Fixed Effects ◽  
Mixed Model ◽  
Polynomial Function ◽  
Random Effect ◽  
Information Criteria ◽  
Polynomial Functions ◽  
Feeding System ◽  
Lactation Length ◽  
Akaike’S Information Criteria

Abstract The objectives of this research were to quantify and model daily feed intakes to 28 d of lactation in modern sows. A total of 4,512 daily feed intake (DFI) records were collected for 156 Hypor sows from February 2015 to March 2016. The mean lactation length was 27.9 ± 2.0 d. The data included 9 parity 1, 33 parity 2 and 114 parity 3+ sows. Data were collected using a computerized feeding system (Gestal Solo, JYGA Technologies, Quebec, Canada). The feeding system was used to set an upper limit to DFI for the first 7 d of lactation. Overall, the least-squares means of a model including the random effect of sow indicated that DFI's continued to slowly increase to 28 d of lactation. The DFI data were fitted to Generalized Michaelis-Menten (GMM) and polynomial functions of day of lactation (t). The GMM function [DFIi,t (kg/d) = DFI0 + (DFIA − DFI0)(t/K)C/[1 + (t/K)C]] was fitted with 2 random effects for DFI (dfiAi) and intercept (dfi0i) using the NLMIXED procedure in SAS®. The polynomial function DFIi,t (kg/d) = [B0 + B1 t + B2 t2 + B3 t3 + B4 t4] was fitted with three random effects for B0, B1, and B2 using the MIXED procedure in SAS®. Fixed effects models of the two functions had similar Akaike's Information Criteria (AIC) values and mean predicted DFI's. The polynomial function with 3 random effects provided a better fit to the data based on R2 30 (0.81 versus 0.79), AIC (14,709 versus 15,158) and RSD (1.204 versus 1.321) values than the GMM function with two random effects. The random effect for B2 in the polynomial function allowed for the fitting of the function to lactation records that had decreased DFI after 15 d of lactation. The random effects for the polynomial function were used to sort the lactation records into three groups based on the derivative of the function at 21 d of lactation. Lactation records of the three groups had similar DFI the first two weeks of lactation (P > 0.40). The three groups of sows had substantially different DFI's after 18 d of lactation (P < 0.028). The differences in both actual and predicted DFI's between the three groups increased with each day of lactation to day 28 (P < 0.001). Mixed model polynomial functions can be used to identify sows with different patterns of DFI after 15 d of lactation.

The Impact of School Leadership and Professional Development on Professional Commitment

2016 ◽  
pp. 260-275
Author(s):  
John K. Rugutt ◽  
Caroline C. Chemosit ◽  
Viviline Ngeno ◽  
Dorothy Soi
Keyword(s):  
Professional Development ◽  
School Leadership ◽  
Hierarchical Linear Modeling ◽  
Secondary School Teachers ◽  
Teaching Experience ◽  
Professional Commitment ◽  
Linear Modeling ◽  
Intra Class Correlation ◽  
The Impact ◽  
Level 2

This study used hierarchical linear modeling (HLM) approach to investigate the impact of school leadership, professional development, gender and teaching experience on professional commitment with a sample of 396 elementary and secondary school teachers and administrators from Kenya. The HLM results indicate significant differences among schools (?2 (49) = 218.92, p<0.001), with an intra-class correlation of 0.3183 indicating that 31.83% of variance in professional commitment was among schools. When professional development and school leadership were used as level 2 predictor variables with no level 1 predictors, the school variability dropped from 4.73584 to 3.30865 indicating that 30.14% of variance in school professional commitment was due to school leadership and professional development (?2 (47) = 161.67, p<0.001). Further, the reliability of the sample means in any school for the true mean school professional commitment was 0.703.

Effects of Compounded Nonnormality of Residuals in Hierarchical Linear Modeling

2021 ◽  
pp. 001316442110102
Author(s):  
Kaiwen Man ◽  
Randall Schumacker ◽  
Monica Morell ◽  
Yurou Wang
Keyword(s):  
Random Effects ◽  
Hierarchical Linear Modeling ◽  
Cluster Size ◽  
Fixed Effects ◽  
Social Science Research ◽  
Parameter Estimates ◽  
Linear Modeling ◽  
Number Of Clusters ◽  
Normality Assumption ◽  
Restricted Maximum Likelihood Estimation

While hierarchical linear modeling is often used in social science research, the assumption of normally distributed residuals at the individual and cluster levels can be violated in empirical data. Previous studies have focused on the effects of nonnormality at either lower or higher level(s) separately. However, the violation of the normality assumption simultaneously across all levels could bias parameter estimates in unforeseen ways. This article aims to raise awareness of the drawbacks associated with compounded nonnormality residuals across levels when the number of clusters range from small to large. The effects of the breach of the normality assumption at both individual and cluster levels were explored. A simulation study was conducted to evaluate the relative bias and the root mean square of the model parameter estimates by manipulating the normality of the data. The results indicate that nonnormal residuals have a larger impact on the random effects than fixed effects, especially when the number of clusters and cluster size are small. In addition, for a simple random-effects structure, the use of restricted maximum likelihood estimation is recommended to improve parameter estimates when compounded residuals across levels show moderate nonnormality, with a combination of small number of clusters and a large cluster size.

scholarly journals A random effects population dynamics model based on proportions-at-age and removal data for estimating total mortality

2012 ◽  
Vol 69 (11) ◽  
pp. 1881-1893 ◽  
Author(s):  
Verena M. Trenkel ◽  
Mark V. Bravington ◽  
Pascal Lorance
Keyword(s):  
Population Dynamics ◽  
Random Effects ◽  
Fixed Effects ◽  
Random Effect ◽  
Total Mortality ◽  
Estimation Bias ◽  
Effective Sample Size ◽  
Dynamics Model ◽  
Population Dynamics Model ◽  
Study Parameter

Catch curves are widely used to estimate total mortality for exploited marine populations. The usual population dynamics model assumes constant recruitment across years and constant total mortality. We extend this to include annual recruitment and annual total mortality. Recruitment is treated as an uncorrelated random effect, while total mortality is modelled by a random walk. Data requirements are minimal as only proportions-at-age and total catches are needed. We obtain the effective sample size for aggregated proportion-at-age data based on fitting Dirichlet-multinomial distributions to the raw sampling data. Parameter estimation is carried out by approximate likelihood. We use simulations to study parameter estimability and estimation bias of four model versions, including models treating mortality as fixed effects and misspecified models. All model versions were, in general, estimable, though for certain parameter values or replicate runs they were not. Relative estimation bias of final year total mortalities and depletion rates were lower for the proposed random effects model compared with the fixed effects version for total mortality. The model is demonstrated for the case of blue ling (Molva dypterygia) to the west of the British Isles for the period 1988 to 2011.

scholarly journals Rhythmic Features of Movement Synchrony for Bonding Individuals in Dyadic Interaction

2019 ◽  
Vol 44 (1) ◽  
pp. 173-193 ◽  
Author(s):  
Ken Fujiwara ◽  
Masanori Kimura ◽  
Ikuo Daibo
Keyword(s):  
Hierarchical Linear Modeling ◽  
Dyadic Interaction ◽  
Wavelet Coherence ◽  
Linear Modeling ◽  
Theoretical Contribution ◽  
Bonding Effect ◽  
Slow Tempo ◽  
Movement Synchrony ◽  
The Impact

Abstract This study examined ways in which rhythmic features of movement contribute to bonding between individuals. Though previous studies have described synchrony as a form of social glue, this research extends those findings to consider the impact of fast versus slow tempo on movement synchrony. This two-part experiment examined dyadic interactions as they occurred between same-sex strangers (Study 1) and friends (Study 2). Participants were video-recorded as they engaged in 5- or 6-min chats, and synchrony was evaluated using wavelet transform via calculations of cross-wavelet coherence. Study 1 employed regression commonality analysis and hierarchical linear modeling and found that among various frequency bands, rapport between individuals was positively associated with synchrony under 0.025 Hz (i.e., slower than once every 40 s) and 0.5–1.5 Hz (i.e., once every 0.67–2 s). On the contrary, Study 2 determined that synchrony of 0.5–1.5 Hz was not impactful among friend dyads and only predictive of the motivation to cultivate a friendly relationship during interactions with strangers. These results indicate the existence of a distinctive rhythm for bonding individuals, and the role of pre-existing friendship as a moderator of the bonding effect of synchrony. However, the role of relative phase (i.e., timing of movement; same versus opposite timing) remains unclear, as the ratio of in- and anti-phase patterning had no significant influence on perceived rapport and motivation to develop relationships. On the basis of the research results, a theoretical contribution is proposed to the study of interpersonal coordination.

Knowledge Sharing, Organizational Climate, and Innovative Behavior: A Cross-Level Analysis of Effects

2013 ◽  
Vol 41 (1) ◽  
pp. 143-156 ◽  
Author(s):  
Chien Yu ◽  
Tsai-Fang Yu ◽  
Chin-Cheh Yu
Keyword(s):  
Organizational Climate ◽  
Knowledge Sharing ◽  
Hierarchical Linear Modeling ◽  
Organizational Innovation ◽  
Positive Association ◽  
Innovative Behavior ◽  
Linear Modeling ◽  
Individual Level ◽  
Innovation Climate ◽  
The Impact

We investigated individual-level knowledge sharing and innovative behavior of employees, organizational innovation climate, and interactions between the individual level of knowledge sharing and the climate of innovation within the organization as a whole. Employees of public corporations in the Taiwanese finance and insurance industries participated in this study. Hierarchical linear modeling (HLM) indicated a positive association between knowledge sharing and innovative behavior and a positive association between organizational innovation climate and innovative behavior. According to the results of HLM organizational innovation climate did not act as a moderator on the impact of knowledge sharing on innovative behavior.

scholarly journals PENGARUH PENYEDERHANAAN STRUKTUR TARIF CUKAI SPESIFIK TERHADAP KONSUMSI ROKOK

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Nur Indah Lestari
Keyword(s):  
Panel Data ◽  
Random Effects ◽  
Random Effect ◽  
Random Effect Model ◽  
Rate Structure ◽  
Price Increases ◽  
Using Data ◽  
Structure Simplification ◽  
The Impact ◽  
Unbalanced Panel Data

ABSTRACT:  This study is conducted to estimate the impact of the increase in regular and specific excise rates structure simplification on cigar's consumption through its price. Using data in 2015 and applying random effect model for unbalanced panel data on Sigaret Kretek Mesin-type and Sigaret Kretek Tangan-type of the cigar, this study compares the impact of price increases due to both specific excise rate structure simplification and regular increase on the excise rate in cigar’s consumption. The results indicate that increase in the specific excise rate structure simplification has a lower impact on raising cigar’s prices than regular excise rate increases. Furthermore, the impact of price increases due to the specific excise rate structure simplification is greater in reducing cigar’s consumption than the price increases due to regular excise rate increases. In addition, it is found that the average price of Sigaret Kretek Mesin-type is lower and has an average consumption that is much higher than Sigaret Kretek Tangan-type. Overall, this result suggests that the specific excise rate structure simplification's policy should be continued in order to reduce cigar's consumption.Keywords: specific excise rate structure simplification, cigar’s consumption, random effects modelABSTRAK:  Penelitian ini dilakukan untuk mengetahui pengaruh kenaikan tarif cukai biasa maupun spesifik terhadap konsumsi rokok melalui harga jual ecerannya. Rokok yang digunakan adalah rokok jenis Sigaret Kretek Mesin (SKM) dan Sigaret Kretek Tangan (SKT). Dengan menggunakan data tahun 2015 dan menerapkan random effect pada unbalanced panel data, penelitian ini membandingkan pengaruh kenaikan harga jual eceran akibat penyederhanaan struktur tarif cukai spesifik dan kenaikan tarif cukai biasa terhadap konsumsi rokok. Hasil penelitian menunjukkan bahwa penyederhanaan struktur tarif cukai spesifik berpengaruh lebih rendah terhadap kenaikan harga jual eceran rokok dibandingkan dengan akibat kenaikan tarif biasa. Lebih lanjut, pengaruh kenaikan harga jual eceran akibat penyederhanaan struktur tarif cukai spesifik lebih besar dalam mengurangi konsumsi rokok dibandingkan kenaikan harga jual eceran akibat kenaikan tarif cukai biasa. Selain itu ditemukan bahwa harga jual eceran rata-rata rokok jenis Sigaret Kretek Mesin (SKM) lebih rendah dan mempunyai rata-rata konsumsi yang jauh lebih tinggi dibandingkan rokok jenis Sigaret Kretek Tangan (SKT). Secara menyeluruh, temuan ini menyarankan agar kebijakan penyederhanaan struktur tarif cukai perlu dilanjutkan karena efektif untuk mengurangi konsumsi rokok. Kata kunci: Penyederhanaan struktur tarif cukai spesifik, konsumsi rokok, random effects model.   

scholarly journals P075 Travel or cheers? Examining the drivers and mechanisms of home court advantage in the 2020/2021 NBA regular season

2021 ◽  
Vol 2 (Supplement_1) ◽  
pp. A45-A45
Author(s):  
J Leota ◽  
D Hoffman ◽  
L Mascaro ◽  
M Czeisler ◽  
K Nash ◽  
...  
Keyword(s):  
Random Effects ◽  
Mixed Models ◽  
Fixed Effects ◽  
Natural Experiment ◽  
National Basketball Association ◽  
Home Team ◽  
The Road ◽  
On The Road ◽  
The Impact ◽  
The Relationship

Abstract Introduction Home court advantage (HCA) in the National Basketball Association (NBA) is well-documented, yet the co-occurring drivers responsible for this advantage have proven difficult to examine in isolation. The Coronavirus disease (COVID-19) pandemic resulted in the elimination of crowds in ~50% of games during the 2020/2021 NBA season, whereas travel remained unchanged. Using this ‘natural experiment’, we investigated the impact of crowds and travel-related sleep and circadian disruption on NBA HCA. Methods 1080 games from the 2020/2021 NBA regular season were analyzed using mixed models (fixed effects: crowds, travel; random effects: team, opponent). Results In games with crowds, home teams won 58.65% of the time and outrebounded (M=2.28) and outscored (M=2.18) their opponents. In games without crowds, home teams won significantly less (50.60%, p = .01) and were outrebounded (M=-0.41, p &lt; .001) and outscored (M=-0.13, p &lt; .05) by their opponents. Further, the increase in home rebound margin fully mediated the relationship between crowds and home points margin (p &lt; .001). No significant sleep or circadian effects were observed. Discussion Taken together, these results suggest that HCA in the 2020/2021 NBA season was predominately driven by the presence of crowds and their influence on the effort exerted by the home team to rebound the ball. Moreover, we speculate that the strict NBA COVID-19 policies may have mitigated the travel-related sleep and circadian effects on the road team. These findings are of considerable significance to a domain wherein marginal gains can have immense competitive, financial, and even historical consequences.

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