Questions tagged [partial]

The partial effect of individual explanatory/predictor variables from a fitted model on a dependent variable.

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Can I partial out covariates with true coefficients known in Logit? [closed]

Suppose the model is $$\ln(\frac{P}{1-P}) = X\beta_0 + A + \epsilon_{ij}$$, and I know $\beta_0$ and thus $X\beta_0$. Think of A as a high-dimensional fixed effect term. Can I partial out the effect ...
31 views

How to test for a partially mediated model?

I have a dataset with three variables: Outcome, Exposure, and Mediator. My hypothesis is that the variables are related as in the following DAG: In particular I want to test that "Mediator" ...
16 views

How do I interpret a partial correlation?

I'm working on a project that has three variables: X, Y, and Z. I suspect, based on my literature review, that X and Y are correlated. However, there is a possibility Z is related to Y as well. I ...
6 views

Short-run effects in a dynamic model with combined variables?

(The models I estimate are actually dynamic panel models. For simplicity of expositon, I abstract from including cross-sectional indexing). The original model that I wished to consider is: y_{t}= \...
216 views

How to calculate percent partial deviance explained by each predictor variable in a GAM model?

I am trying to find a sensible way to calculate the deviance explained by each predictor variable in a GAM model and need some input on my calculations. Following Simon Wood's example on the thread ...
17 views

How to interpret the partial autocorrelation function when non-zero values are preceded by zeros?

I am working with a large number (>500) of partial autocorrelation functions, each for a different time series. I want to be able to quickly identify the likely order of an autoregressive model ...
22 views

difference partial dependence and feature weights

Assume we train a linear model to predict a numeric outcome. A feature's model weight would essentially quantify me how much the outcome variable increases for each increase in the predictor's value. ...
54 views

Multicollinearity and Partial Dependence Questions

Assume I build a binary classification model to predict p(y=1) from {x1, x2, ... x10} For now, assume that model could be a GBM, RandomForest, or Logistic Regression. Also assume that all of the ...
8 views

Partial and Semi-partial/Part correlation in matrix/vector form

For three variables, e.g. $X$, $Y$, and $Z$, it is easy for me to deduce the partial and semi-partial correlation coefficients (in general), however I cannot do the same for more than three variables. ...
21 views

Partial derivative of bivariate cdf

Suppose the bivariate cdf $F(a,b)=Pr(X\leq a, Y\leq b)$ is differentiable in $(a,b)$. Is it true that $\frac{\partial Pr(X\leq a, Y\leq b)}{\partial a}=Pr(X=a,Y\leq b)$?
203 views

is there a R function to do multiple comparison for all levels of a categorical variable by capscale (vegan) with a covariate? [closed]

First, I did DB-RDA for a community dataset with two factors and one covariate. The results showed the interaction effect was significant. Then, I need to do the pairwise comparison for all the levels....
91 views

Partial skewness (kurtosis)

On Wikipedia one can read: In probability theory and statistics, partial correlation measures the degree of association between two random variables, with the effect of a set of controlling random ...
48 views

Which test you recommend?

Assume in a study the dependent variable is quantitative, while most independent variables are categorical, with some of them being quantitative. We aim to evaluate the relationship between the ...
1k views

Standard partial regression plot vs. effect plot from 'effects' package

I'll use a modification of this example to ask my question about an apparent alternative way of presenting a partial regression plot, using the effects package. ...
2k views

Partial dependence plot for glm in r — why linear?

I'd like to understand why my partial dependence plots for a logistic regression model simply show up as straight lines -- even when I'd expect basically a threshold effect from a covariate. I know ...
1k views

Interpretation of partial eta-squared in factorial designs

I'm having troubles interpreting and comparing effect sizes in factorial designs based on partial eta squared values. E.g. in a 3x3-within-subjects design with: η²part, A = .2 η²part, B = .4 η²part, ...
222 views

Quantifying uncertainty when fitting a statistical model to partial effects/dependencies from a random forest (or other machine learning model)

Question: I estimate the partial dependence of $y$ on one predictor in a fitted random forest (RF). I want to now fit a parametric model to this partial dependence. How can I estimate my uncertainty ...
573 views

A null Chi-square test – what could be done next?

I have a rating (from 1 to 5) under two conditions (let’s call them "blue" and "red"). I tested whether the distribution of the ratings is significantly different using a chi squared test for goodness ...
3k views

Generating and interpreting partial dependence plots [closed]

I am trying to mimic partial dependence plots as explained in R's pdp package (https://journal.r-project.org/archive/2017/RJ-2017-016/RJ-2017-016.pdf). The second ...
316 views

Causality Analysis and test of Independence

First the problem: I am refering to lecture note, on page 480, 2nd paragraph, it mentions If X is in fact useless for predicting Y given Z, then an adaptive bandwidth selection procedure (like ...
7k views

How to do partial regression plots with linear mixed-effect models?

I have a linear mixed-effect model in R with two continuous fixed-effects and one random effect, like this: ...
189 views

Partial effects whithout ceteris paribus assumption

Is it possible to estimate the partial effect of the exogenous variables without holding other variables constant, in other words without ceteris paribus assumption? I know that in normal case we need ...
223 views

Partial correlation or two separate correlations? How to interpret?

Hope someone can help me here: So there are variables A, B, C, and D and groups 1 and 2. Groups significantly differ in variables A and B, but not in C and D. From previous research, correlations are ...
23 views

How to report total and complete results

I have conducted a social research with one thousand complete participations and more than 1200 total participations (incomplete contributions included). In reporting the results, what is the best ...
290 views

partial scalar measurement invariance

I have performed a measurement invariance analysis in R using SemTools, to assess the five factor structure of a questionnaire across 3 age groups. The latent variables have 5 indicators (5 items). I ...
4k views

Partial Dependence plot interpretation for Categorical variables

I am using partial dependence plot from random forest. The partial plot doesn't make sense to me. 10th completed people have only 62 out of 933 people as 1. But the partial plot shows positive bar, ...
680 views

Partial/marginal effects after probit regression

Is it plausible to get positive coefficients after running a probit but negative partial/marginal effects? If so, what is the intuition?
207 views

Get covariance from conditional covariance for lognormal (and other) observations?

Consider lognormal random variables $X_1$ and $X_2$ with correlation coefficient $ρ$ and a partial observation sample of them of length N, the sample being partial because it only contains occurrences ...
76 views

How to get the regressed output?

I have a model Y = slope1*variable1 + slope2*variable2 + Intercept. I used lm in R to get slope1, slope2 and Intercept. In this case, variable1 is my main effect ...
2k views

how to plot 3D partial dependence in GBM

I can use the following code to get one-dimensional partial dependence plot. what code can I plot two-variable partial dependence plot, that's the three dimensional figure. Thanks. plot.gbm(GBMmodel,...
2k views

Difference between Partial Correlation and Semi-Partial Correlation

Partial Correlation is when there are three things connected each other(A,B,C), when comparing A and B, we should think about the effect of C so when we calculate the pure relationship between A and B,...
786 views

Why it is popular to use stochastic gradient descent in neural networks rather than the BFGS algorithm? [duplicate]

I have made two solvers to implement neural networks, one is based on stochastic gradient descent (SGD) while the other is based on the BFGS (Broyden-Fletcher-Goldfarb-Shanno) algorithm. I have read ...
723 views

Marginal Effects of Discrete Variables in Quantile Regression

I find myself puzzled by a passage about marginal effects of discrete variables in quantile regression. On p. 217 of Cameron and Trivedi's MUS book, the authors write: For the $j$th (continuous) ...