Background: Isodar analysis allows us to assess the multiple influences of density on relative fitnesses in alternative habitats. It relies on linear regressions. But isodar analyses have a non-classical error structure that complicates the choice of regression method. Prior comparisons of alternative regression methods using simulated data failed to emulate the type of error structure encountered in isodar studies. Question: Which linear regression method gives the most accurate slope and intercept estimates in isodar analyses? Method: Simulate datasets that mimic typical isodar studies but have known functional slopes and intercepts, known levels of measurement error, and known equation error. Generate 50 randomly drawn replicates for eac...
Regression analysis is an important statistical tool for analyzing the relationships between depende...
© 2016, The Author(s). We assessed the ability of several penalized regression methods for linear an...
International audienceThis article and its sequel form an introduction to the field of regression an...
In this review, we describe and illustrate the selection and use of some appropriate regression mode...
Finding association and relationship among measured random variables is a common task in biological ...
Artículo de revisión.In this review, we describe and illustrate the selection and use of some approp...
Linear regression techniques are widely used in atmospheric science, but they are often improperly ...
A common problem that is encountered in medical applications is the overall homogeneity of survival ...
The issue of model selection has drawn the attention of both applied and theoretical statisticians f...
Contains fulltext : 172155.pdf (publisher's version ) (Open Access)BACKGROUND: It ...
It is known that the least square estimator of the slope $\beta$ of the simple regression model $ Y_...
peer reviewedA simulation study has been used to evaluate the minimal error rate of three affectatio...
1. Quantifying individual heterogeneity in plasticity is becoming common in studies of evolutionary ...
Abstract: Robust methods are little applied (although much studied by statisticians). We monitor ver...
The current study proposes a new procedure for separately estimating slope change and level change b...
Regression analysis is an important statistical tool for analyzing the relationships between depende...
© 2016, The Author(s). We assessed the ability of several penalized regression methods for linear an...
International audienceThis article and its sequel form an introduction to the field of regression an...
In this review, we describe and illustrate the selection and use of some appropriate regression mode...
Finding association and relationship among measured random variables is a common task in biological ...
Artículo de revisión.In this review, we describe and illustrate the selection and use of some approp...
Linear regression techniques are widely used in atmospheric science, but they are often improperly ...
A common problem that is encountered in medical applications is the overall homogeneity of survival ...
The issue of model selection has drawn the attention of both applied and theoretical statisticians f...
Contains fulltext : 172155.pdf (publisher's version ) (Open Access)BACKGROUND: It ...
It is known that the least square estimator of the slope $\beta$ of the simple regression model $ Y_...
peer reviewedA simulation study has been used to evaluate the minimal error rate of three affectatio...
1. Quantifying individual heterogeneity in plasticity is becoming common in studies of evolutionary ...
Abstract: Robust methods are little applied (although much studied by statisticians). We monitor ver...
The current study proposes a new procedure for separately estimating slope change and level change b...
Regression analysis is an important statistical tool for analyzing the relationships between depende...
© 2016, The Author(s). We assessed the ability of several penalized regression methods for linear an...
International audienceThis article and its sequel form an introduction to the field of regression an...