An Approach for Determining the Number of Clusters in a Model-Based Cluster Analysis

Akogul, Serkan; Erişoğlu, Murat

doi:10.3390/e19090452

Cited by 154 publications

(120 citation statements)

References 57 publications

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“… Note : An analytic hierarchy process based upon all fit indices presented above from Akogul and Erisoglu (2017) suggested that the 3 class solution was optimal.…”

Section: Resultsmentioning

confidence: 99%

“…The purpose of this study was to evaluate: (a) Whether students that responded positively to a Tier 2 reading fluency intervention belong to distinct profiles based upon their screening score at the beginning of the year and T A B L E 1 Model fit indices for 1-5 class solutions for student response patterns Note: An analytic hierarchy process based upon all fit indices presented above from Akogul and Erisoglu (2017) suggested that the 3 class solution was optimal. Abbreviations: Adjusted BIC, BIC adjusted for sample size; AIC, Akaike information criterion; BIC, Bayesian information criterion; BLRT, Bootstrap likelihood ratio test (p value); % Min, percentage of sample in smallest class; % Max, percentage of sample in largest class.…”

Section: Discussionmentioning

confidence: 99%

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Profiles of reading performance after exiting Tier 2 intervention

Norman

Nelson²,

Klingbeil

2020

Psychology in the Schools

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A fundamental assumption of multi‐tiered systems of support is the bidirectional movement of students between tiers. In comparison to research on when to intensify instruction, less attention has been paid to the validity of decisions to exit students from supplemental supports. We used data from 554 third‐grade students who met the criteria to be exited from a Tier 2 reading fluency intervention to answer two research questions. First, we used latent profile analysis to evaluate whether distinct profiles of student responding would emerge based upon initial skill level and intervention duration. Second, we evaluated whether the proportion of students who passed the end‐of‐year benchmark differed between profiles. Results favored a three‐profile solution with a Below Average Start/Average Response; Average Start/Average Response; and an Above Average Start/Fast Response. The pooled mean proportion of students who did not achieve proficiency on the end‐of‐year benchmark assessment equaled 0.45, 0.33, and 0.13 across the three profiles, respectively. A series of χ2 tests indicated the between‐profile differences were statistically significant (p < .05). The results of this study suggest that there may be distinct profiles amongst students who show positive response and exit Tier 2 reading fluency interventions.

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“… Note : An analytic hierarchy process based upon all fit indices presented above from Akogul and Erisoglu (2017) suggested that the 3 class solution was optimal.…”

Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Profiles of reading performance after exiting Tier 2 intervention

Norman

Nelson²,

Klingbeil

2020

Psychology in the Schools

View full text Add to dashboard Cite

show abstract

“…Information criteria and likelihood ratio tests were used to identify the optimum number of latent classes. We followed an analytic hierarchy process based on the fit indices BI, AIC, AW, CLC, and KIC (60). We also considered the results of the Bootstrap Likelihood Ratio Test [BLRT; (61)].…”

Section: Discussionmentioning

confidence: 99%

A Person-Centered Approach to Prison Behavior Based on Officers’ Observations: Relations to Risk, Prison Misconduct, and Recidivism

2020

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Incorporating measures of prison behavior into risk assessment and management procedures may assist in treatment planning, risk monitoring, and decision-making. A behavior rating scale was used to assess prison officers' observations on externalizing, internalizing, and adaptive behavior in a sample of 277 sexual and violent offenders in correctional treatment in Berlin, Germany. The present study employed latent profile analysis to identify inmate subtypes with similar behavioral patterns. Results indicated a solution with five latent profiles that showed similarities with previous inmate typologies. The subtypes were termed "Aggressive-Psychopathic," "Asocial," "Situational," "Inconspicuous, and "Inadequate-Dependent." Analyses attested to the construct and predictive validity of the subtypes and involved the examination of differences on criminological characteristics, risk assessment instruments, various types of prison misconduct, and postrelease recidivism. This person-centered study illustrates the importance of attending to broader patterns of inmate behavior. The structured assessment of behavioral observations by prison officers can be a valuable and easyto-implement approach to benefit from this largely neglected resource.

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“…The entire dataset is modeled by a mixture of these distributions. One study has applied this method where AHP (Analytical Hierarchy Process) is used to determine the effective number of clusters [13]. SOM (Self-Organizing Maps) is one of Artificial Neural Network architecture which is used for clustering that works with one type of machine learning that is unsupervised learning.…”

Section: Introductionmentioning

confidence: 99%

Assessment of the Average Level of TOEFL Score by using SOM (Self Organizing Map) and K-Mean Clustering Techniques

2019

IJRTE

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Economic growth as measured by GDP growth rates and economic growth set as an increase in GDP strongly helps government predictions about the economic situation and the formation of economic development strategies. This measurement is done by combining mathematical and computer technology to make qualitative and quantitative predictions scientifically and appropriately for economic growth trends. It is a good practical sense to use scientific and proven methods to predict future GDP development trends of a particular economy. In some cases, machine learning methods have proven to be better forecasting results than statistical methods. A Deep Neural Network (DNN) is one type of ANN (Artificial Neural network) architecture based on deep MLP (Multi Layer Perceptron), which uses Deep Learning training techniques. This study proposes the use of DNN to predict the percentage of GDP distribution at current prices by industry sector. In this case, the DNN used will have multiple outputs as many industry sectors. The aim of this study is how to predict for the next period with the smallest possible prediction errors by using DNN.

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An Approach for Determining the Number of Clusters in a Model-Based Cluster Analysis

Cited by 154 publications

References 57 publications

Profiles of reading performance after exiting Tier 2 intervention

Profiles of reading performance after exiting Tier 2 intervention

A Person-Centered Approach to Prison Behavior Based on Officers’ Observations: Relations to Risk, Prison Misconduct, and Recidivism

Assessment of the Average Level of TOEFL Score by using SOM (Self Organizing Map) and K-Mean Clustering Techniques

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