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2
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2answers
77 views

Reporting regression statistics after logarithmic transformation

I'm a bit troubled about how to report linear regression statistics after log transformation of the dependent variable. I suppose I should report the transformed coefficient, but would they be easily ...
0
votes
0answers
17 views

What is data augmented by the additive inverse?

I am reading Biclustering of expression data (Cheng and Church, 2000) The paper is about the Cheng and Church biclustering algorithm and its main metric, the mean squared residue (MSR). It is said ...
1
vote
0answers
19 views

Use of log of an independent variable and its implications

I am currently analyzing the relationship between Google Search frequency and the CDS market. I used a monthly backward rolling regression to determine the 30 search queries which have the biggest ...
2
votes
1answer
59 views

Interaction term in a linear log model

I am using a linear-log model to test whether overseas development assistance and remittances positively affect FDI in cases of good governance and financial market development. Let's say I want to ...
0
votes
1answer
31 views

Expectation operator and logarithmic function

$$\frac{1}{C_t}=E_t\left[\beta \frac{1}{C_{t+1}} \right]R_{t+1}$$ How to log linearise the function? $C_{t+1}$ is the stochastic term; $\beta$ is known.
4
votes
0answers
57 views

Avoiding large variances when taking the logs of small values

I have two random variables $(X$ and $Y)$ that are always positive. The assumption I'm making is that their logs follow normal distributions (i.e., $N(\overline{\log(X)},s^2_{\log(X)})$ and ...
1
vote
1answer
37 views

interpreting the coefficient on a logged independent variable from a probit model

I am using a double model with log transformed independent variables and have calculated average partial effects. Now I am now not sure how to interpret the coefficients; particularly those from the ...
0
votes
1answer
40 views

Best way to estimate a regression with reaction times

I have reactions times in a no-normal distribution, so I am using logarithms. Which can be the best way to estimate a regression? Later, I would like to plot the results according to the age of my ...
1
vote
0answers
33 views

Linear-logarithmic Regression in MATLAB with two input arguments - which model to assume?

Look at the following plot and ignore the solid lines please (just look at the dotted/dashed ones). ONE curve is described by the following parameters and ONE fixed value for the second input ...
7
votes
4answers
1k views

Is it correct to use 'Ln' instead of 'ln' for natural logarithm?

In some research papers, authors use 'Ln' for natural logarithm instead of 'ln'. Is it correct?
2
votes
2answers
83 views

Use logarithmic or linear values when performing correlation and ANOVA?

The data was collected using a logarithmic scale: scores (explanatory variable) are collected with values from 0-5. A score of 3 is 10x the value of a score of 2. I wasn't sure if using either the ...
1
vote
0answers
35 views

Log Transformation in Growth Mixture Model (Mplus user)

I am using parallel process growth mixture modeling to estimate bidirectional longitudinal dynamics between pain (0-100 theoretical range of values) and sleep measures (0-20 theoretical range of ...
0
votes
1answer
90 views

Interpret interactions and logarithms in linear regression

I'm currently playing around with linear regression in R, and I've come up with a regression that fits data quite well. I'm just having some problems with interpreting the coeffiecents of my model. I ...
0
votes
1answer
101 views

Doubt in derivative of logarithm

This seem to silly but I wanted to confirm if the derivative of the log-likelihood $\hskip 2 pt l(x_i)$. The derivative of $$\frac{d (\sum_{i=1}^{M} log(x_i))}{dx} = \frac{1}{x_i} \sum_{i=1}^{M} ...
3
votes
2answers
119 views

Taking the log of variables

Just before I start the question I would like you all to know that I have checked the other threads on taking the log of variables but I still think I have a question that hasn't been touched on yet. ...
2
votes
1answer
52 views

Estimating the effects of cumulative odds ratios - additive or exponential?

I have run some regression models that examine the effect of variable X (a 15 point continuous scale) on Y (a binary variable - not perform/perform a particular behaviour) using logistic regression. ...
4
votes
1answer
39 views

Plotting variables in transformed space

Suppose $A = X_1/X_2$ and $B = X_3/X_4$. Why would one plot the data in $(\log A, \log B)$ space as opposed to $(A,B)$ space?
0
votes
0answers
38 views

How to plug viral coefficient into an exponential growth function?

Is there an exponential growth function that has the viral coefficient(k-factor) as a variable? For example I have 10 initial customers Each invites 10 new customers 20% convert into a new customer ...
0
votes
2answers
72 views

Clarification of log interpretation

Let us say we have this regression $$\ln(y) = a + B_1(age) + B_2\ln(savings) + B_3\ln(income+1)$$ When carrying out the regression we obtain: $$\ln(y) = 0.3445 + 0.5(age) + 0.4556 x_1 + 0.55566 ...
3
votes
1answer
79 views

Performing calculation of a product of a sequence,

I have performed a calculation that a sample of records will contain at least 1 defective record assuming replacement. There are 20,000,000 records in the population, 7,000 are defective, and I will ...
0
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0answers
55 views

Akaike criterion for gaussian mixtures

I am trying to estimate a multimodal gaussian mixture model with an unknown number of nodes. I wish to use a model selection strategy and iteratively test whether incremental modes leads to ...
2
votes
1answer
97 views

Questions on equation of log linear regression

I have been asked to check over a paper. The paper is using log linear regression. In the following log linear equation, $x$ is the dependent variable, $y$ is a continuous covariate, $z$ is a ...
1
vote
1answer
317 views

Bias correction of logarithmic transformations

I read that there is a bias when we transform a series with a logarithm and then applying the inverse function, but only in forecasts of the mean values. I don't understand what it means exactly. ...
0
votes
1answer
393 views

Is it valid to log-transform percentages?

My thesis is to examine the validity of the relationship between tourism represented by tourist exports (real growth) and economic growth using a dummy variable and force workers. I tested the ...
0
votes
0answers
67 views

Variable not significant in log specification

I am estimating a model which gives me significant parameter estimates for my variables of interest. However, when I use the log version of the model log(dependent)=log(independent), I don't get ...
6
votes
1answer
244 views

Binary Models (Probit and Logit) with a Logarithmic Offset

Does anyone have a derivation of how an offset works in binary models like probit and logit? In my problem, the follow-up window can vary in length. Suppose patients get a prophylactic shot as ...
4
votes
1answer
192 views

Why are time-related covariates log transformed in modelling? [duplicate]

I have seen a lot of examples of transforming time-related variables (e.g., age, year, days, etc.), but I don't understand the reasoning behind doing this. I don't think it's for stabilizing the ...
1
vote
0answers
165 views

When analyzing a difference for log-transformed data, when to take the log?

I am working with laboratory data that needs to be transformed due to skewness. It has been gathered at 2 time points and I am interested in the change from time #1 to Time #2. My question is, do I ...
2
votes
2answers
1k views

First difference or log first difference?

I am evaluating the effect of covariances between series on returns. That is I run the following regression: $$ r_t = \beta_0 + \beta_1\text{Cov}(Y_t,r_t) + ...$$ I have conducted my analysis with ...
2
votes
0answers
69 views

OLS standard error log log regression

I am estimating the following Power Law relationship: $$\ln(\text{Rank}) = \text{constant} + \alpha \ln(\text{Size})$$ where $\text{Rank}$ is $1,~2,~3,~...,~n$, and $\text{Size}$ is the raw value. ...
1
vote
1answer
233 views

Plotting 0 in a log scaled axis

I have a very large and sparse dataset of spam twitter accounts and it requires me to scale the x axis in order to be able to visualise the distribution (histogram, kde etc) and cdf of the various ...
5
votes
1answer
1k views

Expected value and variance of log(a)

I have a random variable $X(a) = \log(a)$ where a is normal distributed $\mathcal N(\mu,\sigma^2)$. What can I say about $E(X)$ and $Var(X)$? An approximation would be helpful too.
3
votes
1answer
134 views

Can we use as predictor a variable that was used in the calculation of the dependent (a ratio)?

I wonder if someone could give me some advice on using ratios as a dependent variable in a Generalized Linear Model. I have a variable referring to the increase of "size at Time 1" to "size at Time ...
0
votes
0answers
45 views

What does taking the logarithm of a variable mean? [duplicate]

Possible Duplicate: When are Log scales appropriate? Say you have a bar graph displaying data, for example, "Cost of Computer Orders by Population", and you are trying to analyze the data ...
-5
votes
1answer
99 views

Solving logarithms using variables [closed]

LogQ= a+bLogP+cLogI+dLogPm b= -2.174 c= 0.461 d= 1.909 Determine price elasticity of demand, income elasticity, and cross price elasticity
1
vote
1answer
82 views

multiplicative treatment effects with standard errors

I simplified this a fair bit after finding a draft version of the Imbens and Rubin chapter. I am interested in estimating a constant multiplicative treatment effect from a randomized experiment. I ...
2
votes
1answer
127 views

Fitting ratios in multiple regression formula

I would like to ask a (probably very simple) question with regards to multiple linear regression. I have an experimental formula in the form: $$ Y \sim \frac{a_0 \cdot X_0}{(a_1 \cdot X1) * (a_2 ...
1
vote
1answer
410 views

Logarithmic scale on a plot with negative values

I would like to plot two time-series on a same graph. One series takes much larger values than the other, so I thought a semilog scale might be appropriate (i.e. linear X (dates) and log Y). However, ...
0
votes
0answers
29 views

Interpret natural log transformed dependent variable [duplicate]

Possible Duplicate: Interpretation of log transformed predictor I have a regression equation (below). In the raw form, my Y dependent variable is in days (length of stay in days). I ...
0
votes
1answer
135 views

Elasticity with log + 1

I am running time series regressions to estimate the percentage change in quantity to a percentage change in price, with the most basic form being $\ln Q = \beta_0 + \beta_1\ln P + \varepsilon$, where ...
8
votes
1answer
4k views

Why use logged variables?

Probably, this is a very basic question but I don't seem to be able to find a solid answer for it. I hope here, I can. I'm currently reading papers as a preparation for my own master's thesis. ...
4
votes
2answers
3k views

Logistic regression with an log transformed variable, how to determine economic significance

I am using a logistic regression model with continuous independent variables and two log transformed size variables (total assets and total deposits). My question is how to interpret the results and ...
2
votes
0answers
738 views

Is it mathematically justifiable to log transform variables before running an ANOVA?

I have a model with variables (financial ratios) and some of them are in percentages, some in days and some just ratios (negative and positive). I ran an ANOVA and the results were not so good. When I ...
1
vote
1answer
112 views

The use of logarithmic form to facilitate comparison

On a post from the internet I've found the following expression, which I'll like to understand and to apply it on my datas. "Because of the size difference between the largest and the smallest ...
2
votes
0answers
117 views

Is it possible (or even usefull) to transform Log transformed data into Z-scores?

We have created a questionnaire. In this questionnaire there are different dimensions with different answering scales. Because of our rightly skewed data we log transformed our data. But here is the ...
2
votes
0answers
195 views

Binomial distribution confidence interval for log plot

In simulating iterative decoding of low-density parity-check codes there may be (for a certain signal-to-noise-ratio of a noisy channel) for example 10 decoding failures out of $10^6$ trials. The log ...
1
vote
3answers
3k views

Taking correlation before or after log-transformation of variables

Is there a general principle on whether one should compute pearson correlation for two random variables X and Y before taking their log transform or after? Is there a procedure to test which is more ...
1
vote
1answer
666 views

Base-10 lognormal PDF integrated over log10(x)

From what I understand, the lognormal probability density function in base-10 is mathematically defined thus: $$ p(x; \mu, \sigma) = \frac{log_{10}(e)}{x \sigma \sqrt{2 \pi}} e^{-\frac{(log_{10}(x) ...
1
vote
1answer
1k views

Interpreting a quadratic logarithmic term

Given the regression model $y=\beta_0 + 300*ln(x_1) - 15 * (ln(x_1))^2 + \beta_3*x_2 + ... + u $ $x$ ranges from 1 000 to 30 000 (6.9 to 10.3 on a logarithmic scale). How to interpret the ...
2
votes
2answers
2k views

Transforming the dummy values to be able to take logs

I have a panel data model with double-log functional form. I have 4 variables, one of which is a dummy. What is the best way to transform the values of 0 for my dummy to be able to take natural logs ...