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Conditional logistic regression [PDF]
American Journal of Orthodontics and Dentofacial Orthopedics, 2017 In this article, we will describe how to analyze binary data from matched studies in orthodontics. We have previously discussed matched analysis for paired binary data (McNemar test), but now we will focus on the use of regression methods to model our data.1 The idea is the same as with simple logistic regression models for binary data2,3; however, we ...
Koletsi D, Pandis N
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Robust logistic regression for insurance risk classification [PDF]
, 2001 Risk classification is an important part of the actuarial process in Insurance companies. It allows for the underwriting of the best risks, through an appropriate choice of classification variables, and helps set fair premiums in rate-making.
Garrido, José, Flores, Esteban
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Multicollinearity in Logistic Regression Model -Subject Review- [PDF]
المجلة العراقية للعلوم الاحصائية, 2020 : The logistic regression model is one of the modern statistical methods developed to predict the set of quantitative variables (nominal or monotonous), and it is considered as an alternative test for the simple and multiple linear regression ...
Najlaa Saad Ibrahim +2 more
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Logistic regression diagnostics in ridge regression
Computational Statistics, 2017 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
M. Revan Özkale +2 more
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Oblivious sketching for logistic regression
CoRR, 2021 What guarantees are possible for solving logistic regression in one pass over a data stream? To answer this question, we present the first data oblivious sketch for logistic regression. Our sketch can be computed in input sparsity time over a turnstile data stream and reduces the size of a $d$-dimensional data set from $n$ to only $\operatorname{poly ...
Alexander Munteanu +2 more
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Bias of Maximum-Likelihood estimates in logistic and Cox regression models: A comparative simulation study [PDF]
, 2003 Parameter estimates of logistic and Cox regression models are biased for finite samples. In a simulation study we investigated for both models the behaviour of the bias in relation to sample size and further parameters.
Lenz-Tönjes, Rebecca +7 more
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BarekengThe Public Health Development Index (Indeks Pembangunan Kesehatan Masyarakat - IPKM) is a combined parameter that reflects progress in health development and is useful for determining areas that need assistance in improving health development.
Erwan Setiawan +2 more
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Supporting Regularized Logistic Regression Privately and Efficiently. [PDF]
PLoS ONE, 2016 As one of the most popular statistical and machine learning models, logistic regression with regularization has found wide adoption in biomedicine, social sciences, information technology, and so on.
Wenfa Li +3 more
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On the Complexity of Logistic Regression Models [PDF]
Neural Computation, 2019 We investigate the complexity of logistic regression models, which is defined by counting the number of indistinguishable distributions that the model can represent (Balasubramanian, 1997 ). We find that the complexity of logistic models with binary inputs depends not only on the number of parameters but also on the distribution of inputs in a ...
Nicola Bulso +2 more
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Distributed Parallel Sparse Multinomial Logistic Regression
IEEE Access, 2019 Sparse Multinomial Logistic Regression (SMLR) is widely used in the field of image classification, multi-class object recognition, and so on, because it has the function of embedding feature selection during classification.
Dajiang Lei +4 more
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