Refers generally to statistical procedures that utilize the logistic function, most commonly various forms of logistic regression

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How important is it to include a hypothesis for a report?

I am writing a research report for my final university project. For my analysis I have used logistic regression. I have provided research questions which have been answered. So, how important would ...
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32 views

Converting log odds coefficients to probabilities

Suppose we've ran a logistic regression on some data where all predictors are nominal. With dummy coding the coefficients are ratios of log odds to the reference levels. A colleague claims that we can ...
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What is the posterior probability of the data given the model used for model averaging with Bayesian Logistic Regression?

I am trying to learn about Bayesian Model Averaging using Bayesian Logistic Regression (Genkin, A., Lewis, D. D., & Madigan, D. (2007). Large-scale Bayesian logistic regression for text ...
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Problem with visualising logistic regression using the effects package in R [migrated]

I am using the effects package in R to plot the effects of categorical and numerical predictors in a binomial logistic regression estimated using the lme4 package. My dependent variable is the ...
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55 views

When to divide data into training & test set in logistic regression?

I am using Logistic Regression in a low event rate situation. Overall universe: 46,000 Events: 420 Conventional logistic regression models divide the data into ...
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16 views

Signs on logistic regression betas flip relative to observed - expected counts from chi-squared test

I conduct a chi-squared analysis on some bins and conclude that an association between the bins and an event exists. I then calculate logistic regression coefficients to validate my hypothesis. Also, ...
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Stata's xtlogit (fe, re) equivalent in R?

Stata allows for fixed effects and random effects specification of the logistic regression through the xtlogit fe and xtlogit re ...
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125 views

Difference between regression methods

I have a set of data where the response is a proportion. For each event in the experiment, a system will correctly tag X of Y ...
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25 views

Plot and interpret ordinal logistic regression

I have a ordinal dependendent variable, easiness, that ranges from 1 (not easy) to 5 (very easy). Increases in the values of the independent factors are associated with an increased easiness rating. ...
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26 views

Is segmented (piecewise) regression possible with a dichotomous dependent variable?

I have created a model of American cities with a dichotomous Y variable using logistic regression. I have theoretical reasons to believe that the model will differ significantly between larger and ...
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59 views

Remove effect of a factor on continuous proportion data using regression in R

I have a data set of continuous proportions which depend on a fixed-effect factor, e.g.: ...
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15 views

How to interpret results if a reference category of a categorical variable in multivariable logistic regression is not significant?

I am trying to do a multivariable logistic regression and using a normal binomial logistic regression, using binomial variable X (coded ...
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99 views

How to interpret insignificant categorical variables for logistic regression

I am trying to interpret categorical variables with more than two classes. Some are significant whilst other classes are not. What can I infer from the insignificant ones? Does this mean the ...
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Popular implementations of one vs all logistic regression for mutiple classes in R

Is there any popular implementation of logistic regression in R that defaults to using a one vs all approach for a categorical dependent variable with more than two classes? I have specific reasons to ...
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53 views

Choosing the appropriate method to determine risk factor (logistic regression)

My question is about logistic regression, and I want you to advise me to use the appropriate method for my problem. Here is the description: My goal is to determine the risk factors for a disease (a ...
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21 views

How to subset alternatives in nested multinomial logistic regression?

I am trying to predict whether or not captains in a particular groundfish fishery choose to fish on any given day and what variables may influence that decision. Originally I had planned on using ...
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34 views

How to interpret Weka logistic regression output for a nominal attribute and its coefficients? [closed]

Kindly help me interpreting the output of logistic regression in Weka. I have a data set. Below is the arff file. There is one numeric attribute and 3 nominal ...
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What preponderance of a single outcome renders binary logistic regression ineffective?

This question was motivated, but is separate from, the question I posted here: How can I improve the predictive power of this logistic regression model?. In that case the 'cancer' outcome was ...
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251 views

How can I improve the predictive power of this logistic regression model?

I am using SPSS to analyze a data set which aims to predict whether individuals have cancer based on five symptoms (a, b, c, d, e). In this data set most individuals have cancer. I ran a Binary ...
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1answer
54 views

Choosing between chi-squared / logistic regression vs difference of mean tests for studying bankruptices

You'd expect more companies to go bankrupt if they have low cash balances. Of course, bankruptcies can also happen even when you have lot of cash on hand (to terminate labor contracts, etc.). The ...
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Calculating variable importance at the individual prediction level

I'm trying to build a model which shows the significance of each feature in contributing to the score of each individual prediction. As a dirty hack, I'm running a logistic regression with ...
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Multiclass logistic regression update algorithm

http://web.engr.oregonstate.edu/~xfern/classes/cs534/notes/logistic-regression-note.pdf See section 2 called Multi-class Logistic regression, especially the update rules. (The entire section is only ...
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From logistic regression coefficients to marginal distributions of the dependent variable

I have the coefficients for a logistic regression model with $25$ independent variables of mixed continuous and categorical types. Considering one particular categorical independent variable with $2$ ...
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65 views

confidence intervals for values estimated from the nonlinear regression model

I have a question about nonlinear regression and confidence intervals for values estimated from the model. Here is my problem. I have sets of data where $X$ is the logarithm of the dose of a chemical ...
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Fit and predict logistic regression model for censored data?

Suppose I have a data frame such that: ...
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What does it mean to “fit a regression function” and then use it to update other functions?

Referring to the algorithm on page 11 in this paper on boosting algorithms, I really don't understand step 2, (ii) and (iii). What does this mean: (ii) Fit the regression function $g_j^h (x)$ by ...
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Logistic regression when some variables are measured just for a subset of samples

I have been asked an interesting modelling question by a clinician. The outcome he is trying to predict whether a particular type of cancer will occur. One of the covariates is an indicator variable ...
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Which steps have to be done before fitting logistic curve to time-series?

I want to cluster time-series concerning sales of products. In the database I have 26weeks after launching each products and units sold each week. One of the method of clustering is to cluster ...
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Why is logistic regression a linear classifier?

Since we are using the logistic function to transform a linear combination of the input into a non-linear output, how can logistic regression be considered a linear classifier? Linear regression is ...
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S shaped curve for logistic regression

I was trying to fit logistic regression with a binary response variable and a continuous predictor variable. But when I plotted the fitted probabilities vs the predictor, I got an almost straight line ...
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What is the minimum training set size required for a given number of features for document classification?

For document classification problems, is there a rule of thumb for the number of training instances required for the number of terms in the vocabulary? I am using a logistic regression classifier ...
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How do I run Ordinal Logistic Regression analysis in R with both numerical / categorical values?

Base Data: I have ~1,000 people marked with assessments: '1,' [good] '2,' [middle] or '3' [bad] -- these are the values I'm trying to predict for people in the future. In addition to that, I have some ...
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Partitioning variance from logistic regression

Short version How can I partition the variance from the different levels in a nested mixed-effects logistic regression? Preferably using R, but even general principles would be helpful as a start. ...
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81 views

Adding predicted probabilites from logistic regression instead of using cut value

I am using a logistic regression model to predict a binary decision (purchase, don't purchase) based on several independent variables (income, age, education, etc.) for a population of individuals ...
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17 views

Model selection based on bic.glm function output and K-fold cross validation

I'm looking for a logistic regression model with high prediction power, and the best model returned by the bic.glm function has a posterior probability of 0.348. I ...
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57 views

Understanding coefficients in summary output of logistic regression in R

This question is about understanding the logistic regression output using R. Here is my sample data frame: ...
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Calculating relative importance of independent variables in Linear and Logistic regression

After fitting Logistic/Linear regression model, we get estimates of parameters showing importance of attribute in predicting dependent variable and can be considered as weight of that independent ...
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How do we know which variables (X1,X2,…,X6) are affecting the outcomes (y)?

The data I am using are sales person data. The data contain six independent variables (six vulnerabilities) scored 1-20 and the output is win/loss of the deal. My question is how do we know which ...
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Ranking based on multiple parameters

I am xyz organization. I have recruit entry level engineers from 100 colleges. I have their performance, attrition & promotion data for last 3 yrs. I have 4 parameters performance, promotion, ...
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Criteria for choosing the most appropriate logistic regression model

I've fitted 16 logistic regression models to my data and I'm not sure as to which model to choose as my final model. I looked at a couple of things to help me choose my final model. 1) significance of ...
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Why no mention of penalized regression techniques in Applied Logistic Regression, 3rd edition, by Hosmer, Lemeshow, and Sturdivant?

Just ordered this textbook, and Wow, the complete omission of this subject from an otherwise excellent reference on logistic regression is a bit surprising. The 2nd edition was published in 2000 - ...
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MCA vs Multinomial Logistic Regression

Lets say I have made survey using a sample of a given number of people, containing a set of 25 questions that have 6 possible answers (Fully agree/ Partially Agree/ Neutral/ Partially Disagree/ Fully ...
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What is the difference between forecasting based on ARIMA and logistic curve? R

I'm making a project connected with identifying the dynamics of sales. My database concerns 26 weeks (so equally in 26 time-series observations) after launching the product. This is what my database ...
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Ensemble of models with different feature spaces

BACKGROUND I have data in which the dependent variable is binary with a highly-skewed distribution: <1% records are 1 (doers), >99% records are 0 (non-doers). I'm using logistic regression to ...
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How to calculate p values in logistic regression with gradient descent algorithm

In logistic regression, the gradient descent algorithm for calculating coefficients can be described this way: Until convergence, do $$ \beta := \beta + \alpha \frac{\partial L}{\partial \beta} ...
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Intercept term in logistic regression

Suppose we have the following logistic regression model: $$\text{logit}(p) = \beta_0+\beta_{1}x_{1} + \beta_{2}x_{2}$$ Is $\beta_0$ the odds of the event when $x_1 = 0$ and $x_2=0$? In other words, ...
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Likert Item, Regression analysis

HI there: I have a one likert item I would like to analyze. I know that most scales require multiple likert items, but this is just an exploratory exercise of an existing survey. It's out of my ...
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Odds Ratio Coefficient [duplicate]

Suppose you are given an odds ratio of an interaction term in logistic regression. Is the coefficient associated with this odds ratio simply $\log( \text{OR})$?
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Binary logistic regression

im new to binary logistic regression. I don't know whether the test is giving me real results based on my data set. My dependent variable will be the presence of STEC in fecal samples (Presence= Yes, ...
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Detecting heteroscedasticity - Can I use Breusch-Pagan Test on binary logistic regression?

I'm currently testing a (binary) logistic regression model, which seems to have at least some issues with multicollinearity. Now I don't really trust the data anymore and would like to also test it on ...