Logistic regression - computing log odds without probabiliti, Advanced Statistics

Assignment Help:
Please help with following problem:

: Let’s consider the logistic regression model, which we will refer to as Model 1, given by
log(pi / [1-pi]) = 0.25 + 0.32*X1 + 0.70*X2 + 0.50*X3 (M1),
where X3 is an indicator variable with X3=0 if the observation is from Group A and X3=1 if the observation is from Group B. The likelihood value for this fitted model on 100 observations is 0.0850.
(4) (6 points) For X1=2 and X2=1 compute the log-odds for each group, i.e. X3=0 and X3=1.

Related Discussions:- Logistic regression - computing log odds without probabiliti

Minimization, Minimization is the method or technique for allocating patie...

Minimization is the method or technique for allocating patients to the treatments in clinical trials which is usually the acceptable alternative to random allocation. The procedur

Nested design, Nested design  is the design in which levels of one or more ...

Nested design  is the design in which levels of one or more factors are subsampled within one or more other factors such that, for instance, each level of a factor B happens at onl

Evidence-based medicine (ebm), Described by the leading proponent as 'the c...

Described by the leading proponent as 'the conscientious, explicit, and judicious uses of present best evidence in making the decisions about the care of individual patients, and

Define model, Model is the description of the supposed structure of a set ...

Model is the description of the supposed structure of a set of observations which can range from a fairly imprecise verbal account to, more commonly, a formalized mathematical exp

Omitted covariates, Omitted covariates is a term generally found in the co...

Omitted covariates is a term generally found in the connection with regression modelling, where the model has been incompletely specified by not including significant covariates.

Regression dilution, Regression dilution is the term which is applied when...

Regression dilution is the term which is applied when a covariate in the model cannot be measured directly and instead of that a related observed value must be used in analysis. I

Explain identification keys., Identification keys: The devices for identif...

Identification keys: The devices for identifying the samples from a set of known taxa, which contains a tree- structure where each node corresponds to the diagnostic question of t

Projection pursuit, Projection pursuit is a procedure for attaning a low-d...

Projection pursuit is a procedure for attaning a low-dimensional (usually two-dimensional) representation of the multivariate data, which will be particularly useful in revealing

Histogram, Histogram is the graphical representation of the set of observat...

Histogram is the graphical representation of the set of observations in which class frequencies are represented by the regions of rectangles centred on the class interval. If the f

Write Your Message!

Captcha
Free Assignment Quote

Assured A++ Grade

Get guaranteed satisfaction & time on delivery in every assignment order you paid with us! We ensure premium quality solution document along with free turntin report!

All rights reserved! Copyrights ©2019-2020 ExpertsMind IT Educational Pvt Ltd