MICHAEL FRIENDLY AND DAVID MEYER. Discrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data. Boca Raton, FL: CRC Press.

Biometrics ◽  
2016 ◽  
Vol 72 (2) ◽  
pp. 659-660
Author(s):  
Alan Agresti
Keyword(s):  
Data Analysis ◽  
Count Data ◽  
Discrete Data ◽  
Modeling Techniques

Statistical analysis of the item-count technique using Stata

2019 ◽  
Vol 19 (2) ◽  
pp. 390-434
Author(s):  
Chi-lin Tsai
Keyword(s):  
Data Analysis ◽  
Statistical Analysis ◽  
Count Data ◽  
Profile Likelihood ◽  
Likelihood Estimation ◽  
Great Flexibility ◽  
Recent Developments ◽  
List Experiment ◽  
Experiment Technique ◽  
Item Count Technique

In this article, I review recent developments of the item-count technique (also known as the unmatched-count or list-experiment technique) and introduce a new package, kict, for statistical analysis of the item-count data. This package contains four commands: kict deff performs a diagnostic test to detect the violation of an assumption underlying the item-count technique. kict ls and kict ml perform least-squares estimation and maximum likelihood estimation, respectively. Each encompasses a number of estimators, offering great flexibility for data analysis. kict pfci is a postestimation command for producing confidence intervals with better coverage based on profile likelihood. The development of the item-count technique is still ongoing. I will continue to update the kict package accordingly.

Discrete Data Analysis with R

2015 ◽  
Author(s):  
Michael Friendly ◽  
David Meyer ◽  
Achim Zeileis
Keyword(s):  
Data Analysis ◽  
Discrete Data

scholarly journals Efektivitas Teknik Modeling Dalam Meningkatkan Rasa Percaya Diri Santri di Pondok Pesantren Assalafi Al-Fithrah Surabaya

TRANSFORMATIF ◽  
2018 ◽  
Vol 2 (1) ◽  
pp. 374
Author(s):  
Muhammad Wildan Romdhoni ◽  
Nurul Faizah
Keyword(s):  
Data Analysis ◽  
Character Development ◽  
Problem Formulation ◽  
Control Group ◽  
Control Group Design ◽  
Group Design ◽  
Self Confidence ◽  
Modeling Techniques ◽  
Modelling Techniques ◽  
Development Of Students

<p>This research is motivated by the inequality of character development of students, particularly confidence when speaking in public. This study aims to answer the problem formulation which is reflected in the research hypothesis that modelling techniques effective in increasing the confidence of students in Pondok Pesantren Assalafi Al-Fithrah Surabaya (H<sub>a</sub>). The approach used is a quantitative approach with the research methods true experimental design, pretest-posttest control group design. Samples were taken by purposive from the population are students of class Isti'dad Ulya  A and B. The results of data analysis showed that the modeling techniques effective in improving students confidence when speaking in public in Pondok Pesantren Assalafi Al-Fithrah Surabaya.</p><p class="Abstract"><strong>Keywords</strong>: Modeling Techniques, Self Confidence</p>

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