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1

Mirwan, Dhea Ramadani y Muhammad Nuryatno Amin. "PENGARUH FINANCIAL LEVERAGE, PROFITABILITAS, NET PROFIT MARGIN, DAN UKURAN PERUSAHAAN TERHADAP PRAKTIK PERATAAN LABA". AKUNTABILITAS 14, n.º 2 (28 de julio de 2020): 225–42. http://dx.doi.org/10.29259/ja.v14i2.10982.

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The aim of this research is to prove the effect of financial leverage, profitability, net profit margin and firm size to the income smoothing. Population of this research is manufacturing companies listed at the Indonesia Stock Exchange (BEI) for the period of 2016-2018 with sampling determined by purposive sampling. Data analyzed using logistic regression (binary logistic regresion). The results of this research showed that financial leverage and profitability have negative effect to income smoothing, and at the opposite net profit margin has positive effects to income smoothing. Whereas firm size has no effects to income smoothing
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2

Nuzuliana, Rosmita, Djauhar Ismail y Hikmah Hikmah. "Hubungan status sosial ekonomi dengan perkembangan batita". Jurnal Kebidanan dan Keperawatan Aisyiyah 12, n.º 2 (17 de enero de 2020): 109–17. http://dx.doi.org/10.31101/jkk.303.

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Abstract: This research aims to determine the relationship socialeconomic status (SES) and other influence factor in the last three monthsdue to child development. We used cross sectional design. SSEindicators were parental level of education, montly family income,parental work . We use identity questionnaires and stimulation ofdevelopment questionnaires, Denver II. Analysis methode by chi-squereand logistic regression for multivariate analysis. Research showed thatthe level of education and occupational status did not affect thedevelopment of toddlers. Affecting factor the development of thetoddlers are parents income, gender, playgroup participation, stimulation.Logistic regresion showed that playgroup participant’s and gender weredominant influence factors for child development.
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Duţă, Irina, Simona Fica y Daniela Adriana Ion. "The association between insulin resistance and proliferative retinopathy in type 1 diabetes". Romanian Journal Of Internal Medicine 53, n.º 3 (1 de septiembre de 2015): 261–66. http://dx.doi.org/10.1515/rjim-2015-0034.

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Abstract Introduction. Little is known about the relationship between insulin resistance and proliferative diabetic retinopathy in type 1 diabetes. The aim of this article is to explore the relationship between sight-threatening proliferative diabetic retinopathy and insulin resistance. Methods. This was a cross-sectional study that included 167 type 1 diabetes patients. Insulin resistance was assessed using eGDR (estimated glucose disposal rate) formula. Diabetic retinopathy was assessed by ophthalmoscopy using Early Treatment Diabetic Retinopathy classification. The association between eGDR and proliferative diabetic retinopathy was assessed in uni- and multivariate models using stepwise logistic regression of covariates. The contribution of individual predictors in the final regresion model was examined using Wald statistic. Results. Significantly lower eGDR’s values were observed in patients with proliferative diabetic retinopathy: 5.5 vs. 7 (p = 0.002). The results remained significant (p < 0.001) after adjusting for multiple covariates (sex, diabetes duration, body mass index, HDL cholesterol, LDL cholesterol, triglycerides, smoking). eGDR variable was retained in the final model of stepwise logistic regression (p < 0.001) and showed the strongest association with proliferative diabetic retinopathy (Wald = 12.73). Conclusions. In type 1 diabetes patients insulin resistance was the most important independent risk factor associated with diabetic proliferative retinopathy.
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Elasan, Sadi y Sıddık Keskin. "An application with multinomial logistic regression analysisMultinomiyal logistik regresyon analizi ile bir uygulama". International Journal of Human Sciences 12, n.º 1 (26 de enero de 2015): 443. http://dx.doi.org/10.14687/ijhs.v12i1.3140.

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Řeháková, Blanka. "Kontrasty v logistické regresi [Contrasts in Logistic Regression]". Czech Sociological Review 44, n.º 4 (1 de agosto de 2008): 745–66. http://dx.doi.org/10.13060/00380288.2008.44.4.07.

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Rohmana, Shella Faiz, Agus Rusgiyono y Sugito Sugito. "PENENTUAN FAKTOR-FAKTOR YANG MEMPENGARUHI INTENSITAS CURAH HUJAN DENGAN ANALISIS DISKRIMINAN GANDA DAN REGRESI LOGISTIK MULTINOMIAL (Studi Kasus: Data Curah Hujan Kota Semarang dari Stasiun Meteorologi Maritim Tanjung Emas Periode Oktober 2018 – Maret 2019)". Jurnal Gaussian 8, n.º 3 (30 de agosto de 2019): 398–406. http://dx.doi.org/10.14710/j.gauss.v8i3.26684.

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Meteorologist develop rainfall forecasting methods to obtain better and more accurate rainfall information. One of them is the research of grid data and the method of grouping rainfall. According to BMKG, rainfall is classified into light, medium, and heavy rain. This study aims to determine the factors that influencing rainfall grouping using multiple discriminant analysis with a stepwise selection method. This study uses the daily climate data of Semarang City for period of October 2018 to March 2019. Based on its partial F value, the wind speed variable is eliminated so the significant variable on rainfall grouping are air temperature, air humidity, and wind direction. This analysis produces discriminant scores obtained from linear combinations between discriminant weights and observation values of significant independent variable. The classification procedure is based on the discriminant score each observations compared to cutting score resulted in classification accuracy of 62.89%. Multinomial logistic regression analysis is used to determine the effect of independent variables on rainfall intensity using the odds ratio. This analysis produces an estimate of the conditional probability of each group using significant independent variables are air temperature, air humidity, wind speed, and wind direction. The classification procedure is based on the largest conditional probability value between rainfall groups resulted in classification accuracy of 69.80%. Keywords: multiple discriminant analysis, multinomial logistic regresion, classification accuracy, rainfall
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7

Negreiros-Fransozo, Maria Lucia y Augusto Flores. "ALLOMETRY OF THE SECONDARY SEXUAL CHARACTERS OF THE SHORE CRAB PACHYGRAPSUS TRANSVERSUS (GIBBES, 1850) (BRACHYURA, GRAPSIDAE)". Crustaceana 72, n.º 9 (1999): 1051–66. http://dx.doi.org/10.1163/156854099504013.

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AbstractThe allometric growth of secondary sexual characters in Pachygrapsus transversus is investigated from the 2nd crab stage onward. Clear sexual dimorphism is restricted to abdominal morphology, but ANCOVA analyses showed that chelae become larger in males and the carapace becomes wider in females. Size at the puberty moult in both sexes was estimated using Somerton's computer techniques. Mature II analyses applied to bi-log gonopod length vs. carapace length relationships indicated a puberty moult at 5.0 mm in males. In females, Mature I analyses detected the overlapping growth phase lines in bi-log carapace length vs. abdomen width scatterplots. Fitting the logistic equation provided an estimate of 50% maturity at 5.5 mm. The regression lines separate young and resting individuals from the potentially reproductive females, but they do not separate young from adult crabs. Year-round monthly samples showed that the proportion of small adult-like females is higher during the breeding season. After breeding, females may moult to a young-like morphotype, as observed in controlled laboratory conditions. Moulting to a resting condition splits smaller mature females into different "growth phase" lines. Therefore, estimates of female size at sexual maturity by means of abdomen allometric growth analyses are inadequate in this species. El crecimiento alometrico de los caracteres sexuales secundarios de Pachygrapsus transversus ha sido investigado desde el segundo estadio pos-larval. El dimorfismo abdominal es la unica caracterostica que permite distinguir claramente los sexos, pero los analisis de covarianza aplicados a las regresiones obtenidas demuestran que las quelas se vuelven m as grandes en machos y que el caparazon se vuelve mas ancho en hembras. La talla en que ambos sexos alcanzan la maturidad sexual ha sido estimada atraves de las tecnicas de Somerton. La aplicacion del programa Mature II a la regresion bi-log entre el largo del caparazon y el largo del gonopodo indica que la muda de la pubertad de los machos ocurre a los 5,0 mm. En las hembras, el programa Mature I detecto la sobreposicion de loneas de regresi on en los diagramas de dispersion de la regresion bi-log entre el largo del caparazon y el ancho del abdomen. Del ajuste de la ecuacion logostica se obtiene que 50% de las hembras son sexualmente adultas a los 5,5 mm. Estas rectas de regresion separan las hembras con potencial reproductivo de los indivoduos j ovenes y aquellos en reposo sexual. Sin embargo, las rectas no separan jovenes de adultos. Muestreos mensuales a lo largo de un ano indican que la proporcion de hembras de talla puberal con morfologia adulta es mas elevada durante el peroodo reproductivo. Despues de la reproduccion, estas hembras pueden obtener en la siguiente muda una condicion morfologica semejante a la joven, como fue verificado en condiciones de laboratorio controladas. La obtencion del reposo sexual divide a las hembras de talla puberal en rectas de regresion distintas, por lo que las estimativas de talla a la maturidad sexual atraves del analisis del crecimiento alometrico del abdomen son inadequadas para esta especie.
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Sulistyani, Sulistyani y Deny Ismanto. "ANALISIS RASIO KEUANGAN UNTUK MEMPREDIKSI KONDISI FINANCIAL DISTRESS PERUSAHAAN MANUFAKTUR YANG TERDAFTAR DI BEI". Jurnal Fokus Manajemen Bisnis 7, n.º 2 (13 de febrero de 2020): 156. http://dx.doi.org/10.12928/fokus.v7i2.1744.

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Financial distress precedes bankruptcy. Most financial distress models actually rely on bankruptcy data, which is easier to obtain. The purpose of this research to examine financial ratios that predict financial distress condition of a firm. The sample of this research consist of 14 distress firm and 79 non-distress firms, chosen by purposive sampling. The statistic method which is used to test on the research hypothesis is logistic regresion. The results show that the liquidity ratio (current assets/current liabilities) and a leverage ratio (current leabilities/total asset) is a significant variable to determine of financial distress firms. When profitability ratio (net income/net sales) and price earning ratio (market price per share/earnings per share) are not significant variables to determine of financial distress.
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9

Pir Bavaghar, M. "Deforestation modelling using logistic regression and GIS". Journal of Forest Science 61, No. 5 (3 de junio de 2016): 193–99. http://dx.doi.org/10.17221/78/2014-jfs.

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Indriyanto, Jatmiko, Miftakhul Huda y Ida Afriliana. "Pengembangan Algoritma C4.5 Berbasis Particle Swarm Optimization untuk Penentuan Kelayakan Asuransi". Jurnal Health Sains 2, n.º 3 (23 de marzo de 2021): 427–37. http://dx.doi.org/10.46799/jsa.v2i3.204.

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Tujuan penelitian ini adalah untuk Pengembangan Algoritma C4.5 Berbasis Particle Swarm Optimization Untuk Penentuan Kelayakan Asuransi. metode logistic regresion, decision trees, k-nearest neighbors, naïve bayes dan support vector machines. Model tersebut akan menentukan atau memprediksi status konsumen dimasa mendatang. Observasi yang mirip juga pernah dilakukan, tetapi dengan cara berbeda. Pada penilitian ini, akan digunakan algoritma klasifikasi C4.5 berbasis Particle Swarm Optimization (PSO), hasil ketepatan yang diinginkan lebih bagus dibandingkan hanya memakai algoritma C4.5 untuk mengatasi permasalahan pada kasus pemilihan produk asuransi. dapat disimpulkan bahwa nilai akurasi yang didapatkan pada model algoritma C4.5 berbasis PSO adalah 98.93% lebih bagus jika dibandingkan dengan model algoritma C4.5 yaitu 97.84%. Dari hasil tersebut didapatkan perbedaan antara kedua model yaitu senilai 0.4%. Selagi untuk penelaahan menggunakan ROC curve bagi kedua model ialah,untuk model algoritma C4.5 nilai AUC adalah 0.970 dengan urutan diagnosa Excellent Classification, dan untuk model algoritma C4.5 berbasis PSO nilai AUC adalah 0.968 dengan urutan diagnosa Excellent Classification.
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Triana, Ani. "FAKTOR DETERMINAN TOKSOPLASMOSIS PADA IBU HAMIL". Jurnal Kesehatan Masyarakat 11, n.º 1 (11 de septiembre de 2015): 25. http://dx.doi.org/10.15294/kemas.v11i1.3459.

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<p>Toksoplasmosis merupakan penyakit yang disebabkan oleh Toxoplasma gondii yang merupakan golongan protozoa yang sifatnya parasite obligat intraseluler. Salah satu Provinsi terbesar di Indonesia yaitu Provinsi Riau terdapat kasus Toksoplasmosis yang menurut data dari rekam medis RSUD Arifin Achmad Provinsi Riau toksoplasmosis merupakan penyakit peringkat 9 tertinggi dari 15 penyakit terbesar dalam kehamilan. Tujuan penelitian ini untuk mengidentifikasi faktor determinan terjadinya toksoplasmosis pada ibu hamil di RSUD Arifin Achmad Provinsi Riau. Penelitian ini menggunakan jenis penelitian kuantitatif dengan desain penelitian case control. Populasi pada penelitian ini adalah seluruh ibu hamil yang tercatat di rekam medik RSUD Arifin Achmad pada tahun 2012 dengan jumlah sampel sebanyak 60 orang terbagi menjadi 30 orang sebagai kasus dan 30 orang sebagai kontrol (dengan teknik systematic random sampling). Pengumpulan data dilakukan dengan menggunakan kuesioner data analisis multivariat dengan uji multiple logistic regresion. Hasil penelitian menunjukkan adanya dua variabel yang berhubungan secara signifikan yaitu variabel pekerjaan dengan p value (0,008) OR: 7,97 ; CI 95% (1,70-37,34) dan status paritas dengan p value (0,029) OR: 5,33 ; CI 95% (1,18-24,18).</p><p> </p><p><em>Toxoplasmosis is a disease caused by Toxoplasma gondii is a protozoan group obligate intracellular parasite nature. Riau province there are cases of toxoplasmosis which according to data from medical records General Hospital of Arifin Achmad in Riau Province toxoplasmosis is a disease of the 15 highest ranked 9th largest disease in pregnancy. The purpose of this study to identify the determinants of the occurrence of toxoplasmosis in pregnant women at General Hospital of Arifin Achmad in Riau Province. This research uses quantitative research with case-control study design. The population were all pregnant women recorded in the medical record Arifin Achmad Hospital in 2012 with sample of 60 people divided 30 people as cases and 30 persons as control (with a systematic random sampling technique). Data collection was performed using multivariate analysis of data questionnaire with multiple logistic regresion test. The results presence of two variabels significantly associated job with p value (0.008) OR: 7.97; 95% CI (1.70 to 37.34) and parity status with p value (0.029) OR: 5.33; 95% CI (1.18 to 24.18). Results of the study are expected to health workers to inform about toxoplasmosis complete and CHL counseling and regular prenatal care in the prevention of toxoplasmosis.</em></p>
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12

Rani, K. Sandhya, M. Sai Manoj y G. Suguna Mani. "A Heart Disease Prediction Model using Logistic Regression". International Journal of Trend in Scientific Research and Development Volume-2, Issue-3 (30 de abril de 2018): 1463–66. http://dx.doi.org/10.31142/ijtsrd11401.

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Juliyanti, Wike. "HUBUNGAN PENGETAHUAN IBU, ASUPAN PROTEIN DAN ASUPAN ZINK DENGAN STUNTING (PENDEK) PADA BATITA USIA 12 – 36 BULAN". JURNAL MEDIA KESEHATAN 7, n.º 2 (13 de noviembre de 2018): 198–204. http://dx.doi.org/10.33088/jmk.v7i2.246.

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Stunting (short) is a chronic malnutrition can affect growth of infants and children due to inadequate food intake. The purpose of this study determine the relationship of mother's knowledge, the intake of protein and zinc with stunting (short) in toddlers aged 12-36 months. This study used a cross sectional design. The population is all children under the age of 12-36 months, the sample in this study amounted to 64 people the techniques used are systematic random sampling. Analysis of the data using chi square and logistic regresion test. The results showed that the mother's knowledge there is almost half of the respondents who are less knowledgeable about stunting, protein intake in children aged 12-36 months are almost half less, zinc intake in children aged 12-36 months are almost all respondents less, nutritional status of children 12-36 months of age are most of the stunting, there was no correlation between maternal knowledge and zinc intake with stunting in children aged 12-36 months, and there was association protein intake with stunting in children aged 12-36 months
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14

P, Febrina Nafasati y Dian Indudewi. "PENGARUH MEKANISME INTERNAL CORPORATE GOVERNANCE TERHADAP PEMILIHAN AUDITOR EKSTERNAL". Jurnal Dinamika Sosial Budaya 17, n.º 1 (8 de junio de 2015): 48. http://dx.doi.org/10.26623/jdsb.v17i1.502.

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<p>Mekanisme <em>Corporate Governance </em>memiliki pengaruh terhadap pemilihan auditor eksternal oleh perusahaan. Penelitian ini bertujuan untuk mengetahui pengaruh mekanisme <em>Corporate Governance </em>yang diproksikan dengan kepemilikan saham terbesar, ukuran dewan komisaris, efektivitas komite audit, dan proporsi dewan komisaris independen terhadap pemilihan auditor eksterna pada perusahaan non perbankan . Penelitian ini menggunakan auditor <em>Big 4 </em>dan auditor <em>Non Big 4 </em>sebagai proksi dari pemilihan auditor eksternal yang akan dipilih oleh perusahaan.</p><p>Metode analisis yang digunakan adalah <em>Logistic Regresion. </em>Dimana jumlah sampel yang digunakan dalam penelitian ini adalah perusahaan non perbakan yang terdaftar di Burs Efek Indonesia tahun 2013 sebanyak 177 perusahaan.</p><p>Hasil penelitian menunjukkan bahwa dewan komisaris dan efektivitas komite audit berpengaruh terhadap pemilihan auditor eksternal sedangkan komisaris independen dan kepemilikan saham terbesar tidak berpengaruh terhadap pemilihan auditor eksternal.</p>
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15

Akbar, Rivaldi y Ridwan Ridwan. "PENGARUH KONDISI KEUANGAN PERUSAHAAN, UKURAN PERUSAHAAN, PERTUMBUHAN PERUSAHAAN DAN REPUTASI KAP TERHADAP PENERIMAAN OPINI AUDIT GOING CONCERN PADA PERUSAHAAN PERTAMBANGAN YANG TERDAFTAR DI BURSA EFEK INDONESIA TAHUN 2015-2017". Jurnal Ilmiah Mahasiswa Ekonomi Akuntansi 4, n.º 2 (19 de agosto de 2019): 286–303. http://dx.doi.org/10.24815/jimeka.v4i2.12239.

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This study aims to examine the effect of financial distress, size firms, growth companies, and reputation public accounting firm on acceptance of going concern opinion. The method of this research is a quantitativ approach and SPSS as an analysis tool. Object under study is a mining companies listed on Indonesia Stock Exchange during the periode 2015-2017,as many 33 companies for 3 years with 99 total sample. Testing is done by using logistic regresion analysis by using SPSS version 25.The result showed that the financial distress proxied by the calculation of altman modification model has no significant on the acceptance of going concern audit opinion. Second, the firm size has significant and positive effect on the acceptance of going concern opinion. Third, the growth companies has significant and negative effect on the acceptance of going concern opinion. Finally, the reputation of the public accounting firm proxied at the scale of the public accounting firm has no significant effect on the acceptance of going concern audit opinion
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16

Arisanti, Ike, Isti Fadah y Novi Puspitasari. "PREDIKSI PERINGKAT OBLIGASI SYARIAH DI INDONESIA". JURNAL ILMU MANAJEMEN 11, n.º 3 (1 de agosto de 2014): 1–15. http://dx.doi.org/10.21831/jim.v11i3.11780.

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This study purposes to analyze the influence of financial and non financial factors to prediction of the rating islamic bond in indonesia. The study used independent variable,that is financial factor (growth, size, profit sharing/fee, liquidity) and non financial factor ( secure and maturity) and dependent variable that is the rating of islamic bond. This study applied logistic regresion analysis with sample collection methods using purposive sampling. After selecting fixed criterias, there were 25 islamic bonds chosen with the numbers of 75 investigation from periods of 2010-2012. The result of this study showed that significantly effect the variable growth (X1) , size(X2), profit sharing/ fee (X3), liquidity (X4), secure (X5), maturity (X6) simultaneously to the rating prediction of islamic bond in indonesia. Partially, variable variables of growth (X1) , size (X2), profit sharing/ fee (X3) which referred not significant affecting to the rating prediction of islamic bond in indonesia. Meanwhile, variables of liquidity (X4), secure (X5), maturity ( X6) referred significant affecting to the rating prediction of islamic bond in indonesia.
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17

Juliyanti, Wike. "HUBUNGAN PENGETAHUAN IBU, ASUPAN PROTEIN DAN ASUPAN ZINK DENGAN STUNTING (PENDEK) PADA BATITA USIA 12 – 36 BULAN". JURNAL MEDIA KESEHATAN 7, n.º 2 (13 de noviembre de 2018): 198–204. http://dx.doi.org/10.33088/jmk.v7i2.246.

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Stunting (short) is a chronic malnutrition can affect growth of infants and children due to inadequate food intake. The purpose of this study determine the relationship of mother's knowledge, the intake of protein and zinc with stunting (short) in toddlers aged 12-36 months. This study used a cross sectional design. The population is all children under the age of 12-36 months, the sample in this study amounted to 64 people the techniques used are systematic random sampling. Analysis of the data using chi square and logistic regresion test. The results showed that the mother's knowledge there is almost half of the respondents who are less knowledgeable about stunting, protein intake in children aged 12-36 months are almost half less, zinc intake in children aged 12-36 months are almost all respondents less, nutritional status of children 12-36 months of age are most of the stunting, there was no correlation between maternal knowledge and zinc intake with stunting in children aged 12-36 months, and there was association protein intake with stunting in children aged 12-36 months
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18

P, Febrina Nafasati y Dian Indu Dewi. "Pengaruh Mekanisme Internal Corporate Governance Terhadap Pemilihan Auditor Eksternal". Jurnal Dinamika Sosial Budaya 21, n.º 2 (3 de enero de 2020): 182. http://dx.doi.org/10.26623/jdsb.v21i2.1819.

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<p><em>Internal Coporate Governance Mechanism influence for Auditor Choice. The research is to know of the impact of Internal Corporate Governance Mechanism on auditor choice by non-financial companies, where the proxies of Internal Corporate Governance Mechanism used are the largest shareholder, audit committee’s effectivenese, the number of board of commissioner and the proportion of independent commissioner. This study used Top 4-non Top 4 auditor segregation as a proxy of auditor quality that will be chosen by the company.</em></p><p><em>This study used Logistic Regresion and used 177 of non financial companies listed on the Indonesia Stock Exchange 2013. </em></p><p><em>The Result showed that there are significant of the number of board of commissioner and audit committee’s effectivenese on auditor choice by company. Therea are not significant of the largest shareholder and the proportion of independent commissioner on auditor choice by company.</em></p>
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Hersh, A. y T. B. Newman. "Logistic Regression". AAP Grand Rounds 30, n.º 5 (1 de noviembre de 2013): 55. http://dx.doi.org/10.1542/gr.30-5-55.

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Pagano, Marcello. "Logistic regression". Nutrition 12, n.º 2 (febrero de 1996): 135. http://dx.doi.org/10.1016/s0899-9007(97)85056-4.

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Sedgwick, P. "Logistic regression". BMJ 347, jul12 2 (12 de julio de 2013): f4488. http://dx.doi.org/10.1136/bmj.f4488.

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Sainani, Kristin L. "Logistic Regression". PM&R 6, n.º 12 (diciembre de 2014): 1157–62. http://dx.doi.org/10.1016/j.pmrj.2014.10.006.

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LaValley, Michael P. "Logistic Regression". Circulation 117, n.º 18 (6 de mayo de 2008): 2395–99. http://dx.doi.org/10.1161/circulationaha.106.682658.

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Debanne, Sara M. y Douglas Y. Rowland. "Logistic regression". Gastrointestinal Endoscopy 55, n.º 1 (enero de 2002): 0142–43. http://dx.doi.org/10.1067/mge.2002.119725.

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Debanne, Sara M. y Douglas Y. Rowland. "Logistic regression". Gastrointestinal Endoscopy 55, n.º 1 (enero de 2002): 142–43. http://dx.doi.org/10.1067/mge.2002.120659a.

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26

Tolles, Juliana y William J. Meurer. "Logistic Regression". JAMA 316, n.º 5 (2 de agosto de 2016): 533. http://dx.doi.org/10.1001/jama.2016.7653.

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Grégoire, G. "Logistic Regression". EAS Publications Series 66 (2014): 89–120. http://dx.doi.org/10.1051/eas/1466008.

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Lever, Jake, Martin Krzywinski y Naomi Altman. "Logistic regression". Nature Methods 13, n.º 7 (29 de junio de 2016): 541–42. http://dx.doi.org/10.1038/nmeth.3904.

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Hess, Aaron S. y John R. Hess. "Logistic regression". Transfusion 59, n.º 7 (18 de junio de 2019): 2197–98. http://dx.doi.org/10.1111/trf.15406.

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Davis, Leo J. y Kenneth P. Offord. "Logistic Regression". Journal of Personality Assessment 68, n.º 3 (junio de 1997): 497–507. http://dx.doi.org/10.1207/s15327752jpa6803_3.

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Fearn, Tom. "Logistic Regression". NIR news 11, n.º 2 (abril de 2000): 4–5. http://dx.doi.org/10.1255/nirn.557.

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Wieland, G. Darryl y James Sayre. "Logistic Regression". Journal of the American Geriatrics Society 35, n.º 6 (junio de 1987): 596–97. http://dx.doi.org/10.1111/j.1532-5415.1987.tb01411.x.

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Ostir, Glenn V. y Tatsuo Uchida. "Logistic Regression". American Journal of Physical Medicine & Rehabilitation 79, n.º 6 (noviembre de 2000): 565–72. http://dx.doi.org/10.1097/00002060-200011000-00017.

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34

Novianty, Chentya y Maria C. Widyaastuti. "Pengaruh Moderasi Kepribadian (Big Five Personality) Terhadap Hubungan Akuisisi Informasi dan Perilaku Perdagangan Saham Pada Investor Muda di Indonesia". Media Riset Bisnis & Manajemen 19, n.º 2 (28 de agosto de 2019): 82. http://dx.doi.org/10.25105/mrbm.v19i2.5353.

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<p><strong>Abstrak</strong></p><p><strong>Tujuan </strong>- Penelitian ini bertujuan untuk menganalisis dampak frekuensi akuisisi informasi pada frekuensi perdagangan saham yang dimoderasikan oleh Kepribadian (Big Five Personality).</p><p><strong>Desain/Metodologi/Pendekatan - </strong>Data diperoleh langsung melalui penyebaran kuesioner kepada 304 responden yaitu investor muda (berusia 21 sampai 30 tahun) di Indonesia. Rancangan penelitian yang digunakan dalam penelitian ini adalah Pengujian Hipotesis. Metode analisis yang digunkanan dalam penelitian ini Ordinal Logistic Regresion dengan menggunakan program SPSS.</p><p><strong>Hasil Penelitian</strong> - Hasil dari penelitian ini adalah terdapat hubungan pada akuisisi informasi dan perilaku perdagangan saham, Investor yang tergolong Openness &amp; Neuroticism akan memperlemah hubungan kedua variabel tersebut, sedangkan Conscientiousness, Extraversion dan Agreeableness akan memperkuat hubungan kedua variabel tersebut.</p><p><strong><em><br /></em></strong></p><p><strong><em>Abstract</em></strong></p><p> </p><p><strong><em>Purpose </em></strong><em>–</em><em>This paper was to investigate the impact of the frequency of information acquisition on the frequency of stock trading</em></p><p><strong><em>Des</em></strong><strong><em>ign</em></strong><strong><em>/Met</em></strong><strong><em>hodology</em></strong><strong><em>/</em></strong><strong><em>Approach </em></strong><em>–</em><em> Data </em><em>obtained directly by distributing questionnaires to 304 respondents is young investors (aged 21 to 30 years) in Indonesia. The research design used in this study is hypothesis testing. The analytical method used in this research is Ordinal Logistic Regresion using SPSS program.</em></p><p><strong><em>Findings - </em></strong><em>The results of this study were that there is a positive relationship between information acquisition and trading behavior. Investors belonging to Openness &amp; Neuroticism will weaken the relationship of both variables, while Conscientiousness, Extraversion and Agreeableness will strengthen the relationship of both variables.</em></p><p> </p>
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Fatah, Khwazbeen S. y Rzgar F. Mahmood. "Parameter Estimation for Binary Logistic Regression Using Different Iterative Methods." Journal of Zankoy Sulaimani - Part A 19, n.º 2 (20 de noviembre de 2016): 175–84. http://dx.doi.org/10.17656/jzs.10621.

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Scott, A. J., D. W. Hosmer y S. Lemeshow. "Applied Logistic Regression." Biometrics 47, n.º 4 (diciembre de 1991): 1632. http://dx.doi.org/10.2307/2532419.

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O'Neill, Terence J. y Simon C. Barry. "Truncated Logistic Regression". Biometrics 51, n.º 2 (junio de 1995): 533. http://dx.doi.org/10.2307/2532941.

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Gortmaker, Steven L., David W. Hosmer y Stanley Lemeshow. "Applied Logistic Regression." Contemporary Sociology 23, n.º 1 (enero de 1994): 159. http://dx.doi.org/10.2307/2074954.

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Cucchiara, Andrew, D. Hosmer y S. Lemeshow. "Applied Logistic Regression". Technometrics 34, n.º 3 (agosto de 1992): 358. http://dx.doi.org/10.2307/1270048.

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Flury, Bernard D. y Edward P. Levri. "PERIODIC LOGISTIC REGRESSION". Ecology 80, n.º 7 (octubre de 1999): 2254–60. http://dx.doi.org/10.1890/0012-9658(1999)080[2254:plr]2.0.co;2.

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Koletsi, Despina y Nikolaos Pandis. "Conditional logistic regression". American Journal of Orthodontics and Dentofacial Orthopedics 151, n.º 6 (junio de 2017): 1191–92. http://dx.doi.org/10.1016/j.ajodo.2017.04.009.

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Koletsi, Despina y Nikolaos Pandis. "Ordinal logistic regression". American Journal of Orthodontics and Dentofacial Orthopedics 153, n.º 1 (enero de 2018): 157–58. http://dx.doi.org/10.1016/j.ajodo.2017.11.011.

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Kupper, Lawrence L., David W. Hosmer y Stanley Lemeshow. "Applied Logistic Regression." Journal of the American Statistical Association 85, n.º 411 (septiembre de 1990): 901. http://dx.doi.org/10.2307/2290035.

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Kwak, Chanyeong y Alan Clayton-Matthews. "Multinomial Logistic Regression". Nursing Research 51, n.º 6 (noviembre de 2002): 404–10. http://dx.doi.org/10.1097/00006199-200211000-00009.

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Conklin, Joseph D. "Applied Logistic Regression". Technometrics 44, n.º 1 (febrero de 2002): 81–82. http://dx.doi.org/10.1198/tech.2002.s650.

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Bangdiwala, Shrikant I. "Regression: binary logistic". International Journal of Injury Control and Safety Promotion 25, n.º 3 (3 de julio de 2018): 336–38. http://dx.doi.org/10.1080/17457300.2018.1486503.

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Engel, J. "Polytomous logistic regression". Statistica Neerlandica 42, n.º 4 (diciembre de 1988): 233–52. http://dx.doi.org/10.1111/j.1467-9574.1988.tb01238.x.

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Cantor, Alan B. M. "Understanding logistic regression". Evidence-based Oncology 3, n.º 2 (junio de 2002): 52–53. http://dx.doi.org/10.1054/ebon.2002.0002.

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Meurer, William J. y Juliana Tolles. "Logistic Regression Diagnostics". JAMA 317, n.º 10 (14 de marzo de 2017): 1068. http://dx.doi.org/10.1001/jama.2016.20441.

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Iyer, R., David W. Hosmer y Stanley Lemeshow. "Applied Logistic Regression." Statistician 40, n.º 4 (1991): 458. http://dx.doi.org/10.2307/2348743.

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