Questions tagged [partial-effect]

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

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GLM output says one thing, but glm graph says another, Simpson's Paradox?

I am running a GLM to evaluate the influence of canopy cover and vegetation density on average black-globe temperature. I ran a simple glm, but when I plot the model output, the plot does not agree ...
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Obtain Multiple Regression coefficients from Partial Correlation Coefficients and ANOVA table

I know, that results from multiple linear regression, partial correlation analysis and ANOVA are tightly related to each other. The answers to this and this question indicate that the results may be &...
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Is the PARTIAL regression coefficient always smaller than the SIMPLE regression coefficient (when all variables are positively correlated)?

Suppose we have three variables: X1, X2, and Y. X1 and X2 are the independent variables (IVs) and Y is the dependent variable (DV). Suppose that each IV is positively associated with the DV. Suppose ...
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Interpreting mixed logistic regression probabilities

I have fit a mixed logistic regression, and back-transformed the estimates to a probability scale by calculating the inverse logit. My understanding is that I can interpret this as the change in ...
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Can I partial out covariates with true coefficients known in Logit?

Suppose the model is $$ \ln(\frac{P_{ij}}{1-P_{ij}}) = X_{ij}\beta_0 + A_i + A_j + \epsilon_{ij}, $$ The unit of observation is at $ij$ level, and $A_i$ and $A_j$ are coefficients on the dummy for ...
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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" ...
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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 ...
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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. ...
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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 ...
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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. ...
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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 $\frac{\partial Pr(X\leq a, Y\leq b)}{\partial a}=Pr(X=a,Y\leq b)$?
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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....
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1 answer
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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 ...
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2 answers
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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 ...
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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. ...
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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 ...
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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, ...
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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 ...
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4 votes
3 answers
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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 ...
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2 votes
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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 ...
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1 vote
1 answer
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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 ...
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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: ...
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1 vote
0 answers
207 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 ...
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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 ...
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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 ...
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0 answers
343 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 ...
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1 answer
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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, ...
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2 votes
1 answer
822 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?
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4 votes
0 answers
244 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 ...
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2 votes
1 answer
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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 ...
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1 vote
3 answers
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,...
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1 answer
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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,...
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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 ...
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4 votes
1 answer
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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) ...
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2 votes
1 answer
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Partial sorting: select at most N elements including for sure the top T elements

To whom it may concern. My "population" with known size P is a landscape and has not more than 4 peaks with about same high. Naturally top elements group locally within the population. I seek the top ...
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4 votes
1 answer
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Good machine learning algo for partial derivatives?

Does anyone know of good robust algos to estimate partial derivatives of a regression model? I am talking about a general regression model like this: $\mathbb{E}(y|x_1, x_2, ... x_n) = f(x_1, x_2, ......
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2 votes
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Correlation vs Partial Correlation to explore relationship in data

I have a cognitive architecture solving a set of tasks. Also I have data of human subjects solving the same set of tasks. Now I want to see whether I can find a relationship between the performance ...
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Scatterplot correlation with covariate (partial correlation) in SPSS - how?

I'd like to make a scatterplot of a partial correlation - so a correlation with covariates. How should I do this in SPSS? If necessary, I could also do it in R. The most important thing is to show the ...
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2 votes
0 answers
51 views

How can I test if a bivariate correlation is significantly different from a partial correlation?

I have three variables (A, T, C) with n= 1083. The Pearson correlations are as below: A*T= .170 (p<.01) A*C= .370 (p<.01) T*C= -.103 (p<.01) Partial correlation between A and T ...
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2 votes
1 answer
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How is the proper number of lags for ACF or PACF displaying?

How many lags should be used for ACF or PACF displaying if we have $S$ seasonality? For example, for 500 observations I have 25 lags for 200 observations I have 22 lags It is independent from ...
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6 votes
2 answers
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How are partial regression slopes calculated in multiple regression?

I'm trying to understand how multiple regression statistically controls for the effects of other predictor variables when calculating partial regression slopes. In a multiple regression of Y~X1+X2, ...
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2 votes
2 answers
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Is partial correlation possible after Spearman's correlation?

I have two test groups that conducted an online task measuring response times (avg, avg(congruent), avg(incongruent)). I expected one group to be faster than the other but it turned out exactly the ...
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1 vote
1 answer
18k views

partial eta squared

Would it please be possible to help me with a statistics query. I have asked for the partial eta squared on the output of a one-way within subjects ANOVA from SPSS and it has given me the value .137. ...
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8 votes
1 answer
3k views

how to calculate partial dependence when I have 4 predictors?

I was reading Freidman's book "The elements of statistical learning-2nd edition". Page 365, it talks about partial dependence plot. I don't quite understand how he actually calculates partial depence ...
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3 votes
2 answers
9k views

Is a partial F-Test on a model reduced by only one variable valid?

For a recent project, I used multiple linear regression to model data. I attempted to choose between my initial full model and a reduced model by performing a partial F-test. The models used were the ...
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11 votes
1 answer
8k views

PACF manual calculation

I am trying to replicate the calculation that SAS and SPSS do for the partial autocorrelation function (PACF). In SAS it is produced through Proc Arima. The PACF values are the coefficients of an ...
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3 votes
1 answer
163 views

Differences in coefficients

Suppose I want to see whether $z$ is a confounder for a model with $y$ the outcome variable and $x$ the predictor. If I adjust for $z$, and the adjusted coefficient of $x$ changes versus the ...
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