Evolving High-Tech Collaborations: A Multinomial Logistic Regression Analysis of Innovator Group Size Changes in the Production of Patented Inventions

2012 ◽  
Author(s):  
Richard Gruner
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Group Size ◽  
Logistic Regression Analysis ◽  
Multinomial Logistic Regression ◽  
High Tech ◽  
Multinomial Logistic Regression Analysis ◽  
Patented Inventions

scholarly journals PERBANDINGAN REGRESI LOGISTIK MULTINOMINAL DAN ANALISIS DISKRIMINAN

2021 ◽  
Vol 1 (2) ◽  
pp. 135-150
Author(s):  
Rifda Nabila ◽  
Risdiana Himmati ◽  
Rendra Erdkhadifa
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Discriminant Analysis ◽  
Logistic Regression Analysis ◽  
Multinomial Logistic Regression ◽  
Regression Method ◽  
Destination Image ◽  
Tourism Destination ◽  
Multinomial Logistic Regression Analysis ◽  
Logistic Regression Method

Abstrak: Tujuan dari penelitian ini adalah untuk membandingkan analisis regresi logistik multinomial dan analisis diskriminan untuk mengelompokkan keputusan kunjungan wisata halal di Jawa Tengah berdasarkan ketepatan pengelompokan. Analisis statistik yang digunakan adalah regresi logistik multinomial dan analisis diskriminan. Kedua analisis tersebut dapat digunakan sebagai metode pengelompokan objek, sehingga keduanya dapat dibandingkan berdasarkan ketepatan pengelompokkannya. Penelitian ini membandingkan analisis regresi logistik multinomial dan analisis diskriminan dalam pengelompokan keputusan kunjungan wisata halal. Data yang digunakan adalah worship facilities, halalness, general Islamic mortality, dan tourism destination image. Hasil analisis menggunakan metode regresi logistik multinomial menunjukkan faktor-faktor yang secara signifikan mempengaruhi pengelompokan keputusan kunjungan wisata halal adalah variabel tourism destination image, variabel halalness, dan variabel general Islamic morality. Sedangkan dengan analisis diskriminan menunjukkan bahwa semua variabel prediktor yakni worship facilities, halalness, general Islamic mortality, dan tourism destination image memberikan pengaruh secara signifikan terhadap pengklasifikasian keputusan mengunjungi destinasi wisata halal. Penelitian ini menunjukkan bahwa metode regresi logistik multinomial lebih baik untuk pengelompokkan keputusan kunjungan wisata halal dibandingan metode analisis diskriminan, dengan presetnase ketepatan pengelompokkan pada metode regresi logit multinomial sebesar 59,5%  dan analisis diskriminan sebesar 53,5%. Analisis regresi logistik multinominal lebih mudah digunakan dalam proses pengelompokan keputusan kunjuangan wisata halal karena tidak mempertimbangkan asumsi yang harus dipenuhi. Kata Kunci: Analisis Diskriminan; Regresi Logistik Multinominal; Keputusan Mengunjungi   Abstract: The purpose of this study is to compare multinomial logistic regression analysis and discriminant analysis to classify decisions on halal tourism visits in Central Java based on grouping accuracy. Statistical analysis used is multinomial logistic regression and discriminant analysis. The two analyzes can be used as a method of grouping objects, so that they can be compared based on the accuracy of the grouping. This study compares multinomial logistic regression analysis and discriminant analysis in grouping decisions for halal tourism visits. The data used are worship facilities, halalness, general Islamic mortality, and tourism destination image. The results of the analysis using the multinomial logistic regression method show that the factors that significantly influence the grouping of decisions for halal tourism visits are the tourism destination image variable, the halalness variable, and the general Islamic morality variable. Meanwhile, discriminant analysis shows that all predictor variables namely worship facilities, halalness, general Islamic mortality, and tourism destination image have a significant influence on the classification of decisions to visit halal tourist destinations. This study shows that the multinomial logistic regression method is better for grouping decisions on halal tourist visits than the discriminant analysis method, with a preset percentage of grouping accuracy in the multinomial logit regression method of 59.5% and discriminant analysis of 53.5%. Multinominal logistic regression analysis is easier to use in the process of grouping halal tourism travel decisions because it does not consider the assumptions that must be met. Keywords: Discriminant Analysis; Multinomial Logistic Regression; Visiting decision.

scholarly journals Comparative analysis of the elements of attack and defence in men’s and women’s games in the Estonian volleyball highest league

2016 ◽  
Vol 25 (1) ◽  
pp. 37 ◽  
Author(s):  
Raini Stamm ◽  
Meelis Stamm ◽  
Doris Torilo ◽  
Kaivo Thomson ◽  
Alexander Jairus
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Comparative Analysis ◽  
Logistic Regression Analysis ◽  
Multinomial Logistic Regression ◽  
Block Type ◽  
Multinomial Logistic Regression Analysis ◽  
Expert Assessments ◽  
Attack Type

The aim of this study was to analyse the differences between men’s and women’s teams of the Estonian highest league in attack, serve, block, defence and serve reception. The sample consisted of 5 men’s and 5 women’s teams of the Estonian volleyball highest league in the 2014/2015 season. To collect data, two game videos of each team were watched; from them tempo of attack, type of attack, block and serve, and the results of defence and cover were registered. In addition, statistics created by the Data Volley and Volleysoft 6–3 programs on the basis of expert assessments were used to estimate the efficiency of volleyball elements and results of reception. SPSS Statistics 23 version for Windows was used to construct frequency tables and multinomial logistic regression analysis was applied to find the probable frequencies of the activities analysed. The results revealed that in Estonian men’s highest league games quick tempo 1 attacks were used statistically significantly more often than in women’s games. Men were more proficient at attack and used a vigorous spike more often than women. For both genders, double block was the most often used block type. Broken double block was more common to men than to women. The serve type most often used by men was the power jump serve, followed by the tactical float serve. Women most often used the standing serve and, as second, the jump float serve. Men made more serve errors than women did. The percentage of ace serves was also higher in women than in men.In defence, the percentage of the ball remaining in play was higher in women than in men, and women’s defence cover was more efficient than men’s. As a result of attack cover, the ball remained in play nearly by half more frequently in women’s than in men’s games. Nonetheless, women scored fewer points as a result of attack cover. Serve reception in the Estonian highest league was better in men, and men made statistically significantly fewer errors in reception than women did.

scholarly journals Patterns of gender assignment in the Jamtlandic variety of Scandinavian

2019 ◽  
Vol 43 (1) ◽  
pp. 93-125
Author(s):  
Briana Van Epps ◽  
Gerd Carling
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Multinomial Logistic Regression ◽  
Word List ◽  
Gender Assignment ◽  
Multinomial Logistic Regression Analysis ◽  
Biological Sex ◽  
Language Variety ◽  
Masculine Gender

AbstractIn this study, we present an analysis of gender assignment tendencies in Jamtlandic, a language variety of Sweden, using a word list of 1029 items obtained from fieldwork. Most research on gender assignment in the Scandinavian languages focuses on the standard languages (Steinmetz 1985; Källström 1996; Trosterud 2001, 2006) and Norwegian dialects (Enger 2011, Kvinlaug 2011, Enger & Corbett 2012). However, gender assignment principles for Swedish dialects have not previously been researched. We find generalizations based on semantic, morphological, and phonological principles. Some of the principles apply more consistently than others, some ‘win’ in competition with other principles; a multinomial logistic regression analysis provides a statistical foundation for evaluating the principles. The strongest tendencies are those based on biological sex, plural inflection, derivational suffixes, and some phonological sequences. Weaker tendencies include non-core semantic tendencies and other phonological sequences. Gender assignment in modern loanwords differs from the overall material, with a larger proportion of nouns assigned masculine gender.

scholarly journals Impact of the COVID-19 pandemic on the development of locomotive syndrome

2021 ◽  
Vol 29 (3) ◽  
pp. 230949902110609
Author(s):  
Hidetomi Terai ◽  
Yusuke Hori ◽  
Shinji Takahashi ◽  
Koji Tamai ◽  
Masayoshi Iwamae ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Musculoskeletal Disorders ◽  
Logistic Regression Analysis ◽  
Multinomial Logistic Regression ◽  
Multiple Logistic Regression Analysis ◽  
Locomotive Syndrome ◽  
Exercise Habits ◽  
Multinomial Logistic Regression Analysis

Background The coronavirus disease 2019 (COVID-19) pandemic has affected people in various ways, including restricting their mobility and depriving them of exercise opportunities. Such circumstances can trigger locomotor deterioration and impairment, which is known as locomotive syndrome. The purpose of this study was to investigate the incidence of locomotive syndrome in the pandemic and to identify its risk factors. Methods: This was a multicenter questionnaire survey performed between 1 November 2020 and 31 December 2020 in Japan. Patients who visited the orthopedics clinic were asked to answer a questionnaire about their symptoms, exercise habits, and locomotor function at two time points, namely, pre-pandemic and post-second wave (current). The incidence of locomotive syndrome in the COVID-19 pandemic was investigated. Additionally, multiple logistic regression analysis was used to identify the risk factors for developing locomotive syndrome during the pandemic. Results: A total of 2829 patients were enrolled in this study (average age: 61.1 ± 17.1 years; 1532 women). The prevalence of locomotive syndrome was 30% pre-pandemic, which increased significantly to 50% intra-pandemic. Among the patients with no symptoms of locomotive syndrome, 30% developed it in the wake of the pandemic. In the multinomial logistic regression analysis, older age, deteriorated or newly occurring symptoms of musculoskeletal disorders, complaints about the spine or hip/knee joints, and no or decreased exercise habits were independent risk factors for developing locomotive syndrome. Conclusions: The prevalence of locomotive syndrome in patients with musculoskeletal disorders has increased during the COVID-19 pandemic. In addition to age, locomotor symptoms, especially spine or hip/knee joint complaints, and exercise habits were associated with the development of locomotive syndrome. Although the control of infection is a priority, the treatment of musculoskeletal disorders and ensuring exercise habits are also essential issues to address during a pandemic such as COVID-19.

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