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1 vote

How to interpret an index of values between -2.5 and +2.5 (an independent variable) in a regression?

Look at this post to see how to normalize between 0, 1 with Stata. And this post for the general idea. The coefficient for f_opennavg is $-0.261$, so assuming your ...
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Isolating a relationship's significance

Since your dependent variable (W) is Binary, you could consider the Logistic Regression approach. The Logistic Regression coefficients are in terms of log-odds and you can easily derive the odds or ...
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1 vote
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Repeated measures ANCOVA interpretation – significant covariate/test day interaction

Instead of getting caught up in ANCOVA terminology, remember that it's just a particular form of a linear regression model. With ANCOVA, you have a continuous outcome (here, ...
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Interpreting Significant Interaction Term Odds/Hazard Ratio with Binary Variables

The correct answer (assuming that you are using treatment or dummy coding for each of A and B) is close to your second suggestion, with one modification: the interaction between A and B provides a ...
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9 votes

What is the correct interpretation of the $\beta_1$ coefficient in a linear regression model?

Here is what $E[Y|X]$ changes when $X$ changes by one unit (using that the expectation operator is linear and that $\epsilon$ is independent of $X$ with $E[\epsilon] = 0$): $$ \begin{align} E[Y|X = ...
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1 vote
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LMM Results interpretation: Change in results when adding interaction

Under treatment/dummy coding as you are using, this is what happens with coefficients when predictors are involved in interaction terms. The individual coefficient for a predictor is then defined for ...
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Interpret multiple logistic regression

The interpretation of fitted regression coefficients $\beta_i$ as causal effect requires some additional insight into your scenario. E.g., if you know for sure that your variable Intervention is not ...
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1 vote
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Convert T-values from Poisson regression to Standard Errors

I contacted a statistics professor at my faculty and the author of the paper - the solution is: SE_logIRR = log(IRR)/Tvalue and the example calculation becomes: SE_logIRR = log(0.76)/1.96 = -0.14002 ...
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4 votes
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Interpretation of interaction of a continuous and a dummy variable in linear regression

$\beta_3$ is the difference in slopes of $\mathbb{E}(Y|X_1)$ vs. $X_1$ between observations that have $D=1$ and these that have $D=0$. The slope for the former is $0.5+0.7=1.2$ and for the latter $0.5$...
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Interpretation of log-linear regression

Both sources give you a different interpretation of log-linear models. The first source gives the interpretation in terms of the percentage change. That is, $ (e^\beta - 1) * 100 $ shows the ...
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Interpret the impulse response when define shocks in terms of variances of the residual of the equation

According to the linked article, the first equation is describing the output gap $y$, defined as the difference between actual logGDP $Y:=\log X$ and potential logGDP $\bar{Y}:=\log\bar{X}$, so $y = \...
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Should a covariate be lagged in a GARCH-X model?

How can I interpret those results? Interpretation of a GARCH(1,1) is textbook material; it should not be hard to find. At the same time, there is not much to it. The model specifies that the current ...
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2 votes

Is this a correct interpretation of percent importance?

In contrast to frank, I think this method is potentially useful. I think we can reasonably disagree here. I am less concerned with what frank sees as a problem: since you already look at multiple ...
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4 votes

Is this a correct interpretation of percent importance?

I would be careful with this method. Usually, the importance attribute given by a model only refers to this model, i.e. it is just saying that, for this particular model, this column has this special ...
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Interpreting categorical variables with reference level in linear model

This is really a FAQ---but so far no good reference (duplicate) answer. The short answer is that the omitted reference level has an implied coefficient of zero. It would be useful if software ...
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Linear Connected Layer before the DNN

In your proposed architecture, the weights to the second and to the third layer are arbitrary. If you divide the weight $w^1_i$ to the $i$-th node in the second layer (for the connection from the $i$...
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4 way mixed ANOVA--Need help interpreting a 3 way interaction!

A significant 3-way interaction (here among all of the within-subject variables) means that you can't properly assess the association between any one of those predictors and outcome unless you know ...
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P trend and association

This terminology is unlikely to be specific to a Cox model. A p-value "trend" usually refers to a p-value that was almost less than the usual 0.05 cutoff value. This term is used by some ...
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Mixed model fixed effect interpretation doubt

IIUC, your variable timep is currently a factor. Since you want "each subject to have different starting points and different linear changes over time", ...
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