Questions tagged [log-linear]
The log-linear model is a form of Poisson regression that allows for the analysis of multi-way contingency tables.
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Log-linear regression: interpretation of RSE
AIM: To really, really understand what the model outputs mean in a log-linear regression, specifically, how to interpret the residual standard error (RSE).
I have read this post but it does not ...
2
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1answer
35 views
Confidence interval of a log-linear regression
AIM: Make a confidence interval statement on a log-linear regression
I have read posts like:
Interpreting Standard Deviation of Natural Log Transformed Data
Lognormal Regression?
But they do not ...
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0answers
15 views
INTERPRET A REGRESSION MODEL WHEN OUTCOME VARIABLE IS LOG TRANSFORMED [duplicate]
I have used a linear model between a log-transformed outcome variable and a group of predictor variables. In this model, the dependent variable is in its log-transformed state, and the independent ...
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7 views
Log-linear BIAS adjustment
I have a loglinear model of:
$log(\mu(S_{ij|gij}))=\alpha_0+\alpha_1g_{ij}$
where gij is distance, and Sij is connectivity
There is a bias in the distribution of count values for the outcome ...
0
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0answers
29 views
Poisson log linear Regression: using either R or python
I was hoping someone can help me with this problem. I posted a similar question earlier but it's not the same.
I have the following:
A 2x2 matrix of structural connectivity values between brain ...
2
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2answers
104 views
Interpretation of β in case of log-lin model for relationship between X and Y
In many papers, the dependent variable is transformed by taking natural log. For instance, consider the following model:
$$\newcommand{\Cov}{{\rm Cov}}
\ln(\text{Y}) = \alpha + \beta\, X_1 + \epsilon
...
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1answer
28 views
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27 views
Logistic regression and log-inear
I do not know why log-linear is non-sensitive margins and logistic regression is sensitive margins. Both are using odds ratios Can anyone give some explanation.
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1answer
224 views
Predicting probabilities after log-linear regression
I would like to estimate a log-linear regression and examine the results with Stata's marginsplot command. I have transformed my dependent variable into natural logarithm (to make a highly skewed ...
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1answer
141 views
Check log-linearity of a continuous variable to predict survival
I have the following survival data: cases with a continuous variable risk_factor wich higher values having a higher HR (1.026, CI: [1.017-1.034], p = 2.03e-09) for ...
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0answers
19 views
What is the appropriate analysis for this type of repeated measures multi-binary data?
There is a popular theory within psychology that certain emotions will trigger "prototypical" facial expressions defined by the simultaneous contraction of specific facial muscles. For example, if a ...
3
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1answer
64 views
Log-linear regression preferred over logistic regression for categorical vars?
I read here that, when all variables are categorical, log-linear is preferred over logistic regression "because log-linear is merely an extension of the chi-square test." I don't have a stats ...
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27 views
Conceptual question about log-linear analysis
I have measured the binary occurrence of three types of events on multiple days. Theory suggests that these events are not independent and should occur on the same days more than would be expected ...
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71 views
Difference between PROC CATMOD and PROC GENMOD for log-linear regression
I am reading "An Introduction to Categorical Data Analysis, Second Edition" by Alan Agresti. Data I am trying to fit is presented in Table 7.3 in the book. The log-linear regression by PROC GENMOD is ...
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1answer
60 views
How do I interpret the coefficients of a log-linear regression with quadratic terms?
I have a regression equation of this kind:
$$\log {y} = a + bx + cx^2 + \epsilon$$
where $a$ is the intercept, $b$ and $c$ are the coefficients of $x$ and $x^2,$ and $\epsilon$ is the error. How do ...
0
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0answers
49 views
Log-linear analysis versus independent chi-squares result
I am analyzing a number of categorical variables, and used log-linear modeling in SPSS to see whether there is association between any of them. I have some variables, however, which turn out to be non-...
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2answers
169 views
How can I interpret intercept when my dependent variable is in log form?
My model consists of both log independent and dependent variables, and percentage share, as well as number of people and etc. My dependent variable is log(GPD per capita in USD), my statistic package ...
0
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1answer
43 views
Newton-Raphson Error
According to Agresti(2013) pg 364-365, iterative methods such as Newton-Raphson methods, $
\begin{aligned}
\beta^\text{new} &= \beta^\text{old} + (X^{T}WX)^{-1}X^{T}(V)
\end{aligned}
$ help to ...
2
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0answers
93 views
Log-normal vs. log-linear vs. logging the response variable
I've been reading a lot of Wikipedia pages and StackExchange/CrossValidated posts, and I have come to a point where I realize I do not understand some of the terminology I have been using.
What's ...
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0answers
54 views
calculate P-value loglinear coefficient marginal models fitted with maximum likelihood
i am using the cmm package in R to fit graph models between 4 categorical dummy variables of interest such that
A is marginal independent from B
B is conditional independent from A and B given D.
I ...
3
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1answer
183 views
How are graphical models “a subset of log-linear models”?
Caveat lector: I am not sure what is meant by a "log-linear model". The Wikipedia page makes it seem as if log-linear model is an alternative term for exponential family.
This description of a book ...
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1answer
65 views
Log-linear model vs Multinomial-Dirichlet model for contingency table
Given a 1x3 contingency table of the form
$$[y_1,y_2,y_3]$$
where each $y_i$ represents a count on some random variable $$X\sim Multinomial(n, \pi_1,\pi_2,\pi_3)$$
We can estimate the vector of ...
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2answers
684 views
Poisson regression vs log-linear model
I'm confused about the difference between log-linear model and poisson regression and I am not sure which one to use to answer my research question.
In the experiment, participants were grouped into ...
2
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1answer
110 views
What does it mean if the residuals for a log-linear model are all zero?
Probably a very basic question, but I have a contingency table formed of 3 categorical variables (one with 3 levels, the rest with 2) and have been asked to try to test the association between them ...
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0answers
90 views
How is a covariate added to a log-linear model?
There are a number of good Q/As about log-linear models (i.e., here). The data I am analyzing is off shifts between categories, 0, ...
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0answers
125 views
Bootstrapping in contingency table
I have categorical data represented by a two-way contingency table (say $Y_{1}$ and $Y_{2}$, each with three levels). The data consists of fully observed counts (where data on both $Y_{1}$ and $Y_{2}$...
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0answers
36 views
Present difference in estimates for positively-skewed continuous outcomes
I'm working with a dataset containing results from two types of cognitive tests:
Pairs-matching test (say, $Y_1$), which recorded as number of incorrect matches (discrete count of mistakes, ranging ...
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0answers
664 views
semi-log (log linear) regression model
I know there are different reasons for choosing a particular model (e.g. log log, semi log, lin log).
I read somewhere that the semi log (where only the log of Y is taken) corresponds to a ...
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0answers
51 views
Real-world implications of categorical interactions
I'm studying the interaction of three categorical variables but I'm struggling to explain what the interactions mean in real-world terms. The three variables each have two levels (yes/no). They are:
...
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1answer
44 views
Is there a multiple regression model with both percentage and unit changes in $Y$?
In a standard linear model, $Y = \beta_0 + \beta_1 X_1 + \beta_2 X_2$, a unit increase in $X_1$ leads to a $\beta_1$ increase in $Y$ (likewise for $X_2$).
In a log-level model, $\ln(Y) = \beta_0 + \...
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0answers
52 views
Distinguish 2-way and 3-way interactions in binary data, independent of reference category
$\newcommand{\P}{\mathbb{P}}$I have three variables $X_a, X_b, X_c \in \{0, 1\}$ and I define a joint distribution:
$$
\P(X_a, X_b, X_c) \propto \exp
\left \{
\theta_{abc} \mathbb{I}_{\{X_a = 0 \...
2
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1answer
109 views
Effect Size log linear model when predictor is in percent
When performing a linear regression with a log-transformed dependent variable, one has to exponentiate the estimated coefficient of a predictor, subtract it by one and multiply it by 100 in order to ...
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0answers
81 views
Analysing count data for within-subjects design
I have the following experimental design but I'm not certain which analysis I should use to test my claim:
I have a binomial outcome (correct, false = 1, 0). Each participant takes three questions, ...
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1answer
568 views
Log-linear regression vs. Poission regression
In this post, OP asked the difference between log linear regression and logistic regression. Two answers in the post are very clear and directly address OP's question.
I understand Log-linear ...
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0answers
123 views
On the (wrong?) interpretation of log-linear models
For simplicity, let $X$ be a continuous random variable and assume that
${E}[\ln(Y)|X] = \beta X$, i.e., the conditional expectation of $Y$ given $X$ is proportional to $X$.
According to many ...
6
votes
1answer
154 views
What distribution to fit if the log of log is still convex?
I am trying to fit a model with variable x, and y. plot(x, y) shows that it is convex (downward) and decaying which makes me think I need to make a log ...
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0answers
148 views
Log-linear analysis of transition matrices using R
I have some demographic transition matrices that I want to compare using a log linear analysis, but am having some trouble with model construction in R. I have read through several tutorials on log-...
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2answers
249 views
Check for endogeneity
I run a log linear model, as $log(y) = b_0 + b_1x_1 + b_2x_2 + e$. I think $x_1$ may be endogenous and I would like to test it, so that I can consequently run a two-stage model. I would like to know ...
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0answers
160 views
Analysing categorical variables across several categories (LogLinear analysis?)
I'm editing this question in hopes of improving it, and thus receiving some advice on it.
I have collected info on diet from several populations. There are different groups (e.g. ElMolo) made of ...
3
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1answer
197 views
Nonlinear regression for a log-linear model
I have data points $(x_i, y_i), i = 1, \dots, N$, and a model (log-linear) with parameters $w_j, j = 0, \dots, m$ such that $y_i=\alpha_i e^{w_0+w_1x_i+w_2x_i^2+\dots+w_mx_i^m}+ n_i$, where $n_i$ are ...
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0answers
36 views
Bacteria counts in petri dish confusion
I'm currently (attempting) to help a fellow student with some statistical analysis. Basically she is looking at the effect of a sugar treatment on bacterial growth within a petri dish.
She has three ...
2
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1answer
228 views
What's the difference in growth of Y in a linear regression model when using a log-lin model or a lin-log model
Description
I'm currently studying a chapter on linear regression analysis. I have come to a section where we study the interpretation of the coefficients with logarithmically transformed variables. ...
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0answers
31 views
I want to find contributions of each independent variables
I would like to get contributions of independent variables (factors driving sales) in absolute dollar values.
The log linear equation looks like this:
$$\ln(\text{sales})=b_1 \times \ln(\text{...
2
votes
1answer
110 views
Multivariate Log-linear Model
I know from here that a log-linear model can be used to estimate a conditional probability of class $c$ given the feature representation $d$ of datapoint $x$.
$p(c|d;\theta) = \frac{exp(\theta.d_c)}{\...
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2answers
174 views
Applied interpretation of coefficients of log linear regression model
I'm in the process of using a log-linear transformed OLS model to predict the impact of temperature changes on sales.
I know that the interpretation of a log-linear model loosely follows as: for each ...
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1answer
1k views
What is the difference between Poisson Regression and Log-linear Models in terms of their usage and which should I use?
I'm currently analyzing a data set from an experiment, where participants could give one of three types of answers: 1) Correct, 2) incorrect-congruent, 3) incorrect-incongruent. The priming ...
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1answer
1k views
offset in glm for poisson regression
The offset argument in the glm() quite troubles me. As below, m3 is the usage of offset that I have seen. m4 is a manually calculated analog. But the result obtained is completely different, with m3 ...
0
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1answer
421 views
Log-linear model, Poisson regression, categorical variable with 100 levels
I want to compare the incidence rate(asum) of 100 different cities(cityID) to see if there are significant differences among them. Given that the incidence rate is following Poisson, so it is a log-...
0
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1answer
75 views
problem with the relationship between log linear and logistic regression models
I am supposed to fit a logistic regression model and the find the log- linear model which correspond to it, fit that model and show the correspondence between parameters. But it is not working, I am ...
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0answers
111 views
Converting Dirichlet distribution to distribution on the log-linear parameters
Dirichlet prior/posterior provides a probability density on distributions over a multinomial variable. It has the form :
$P(P) \varpropto \prod_i{P_i^{\alpha_i-1}}$
I can also describe the ...
