![]() ![]() I would like to extract the estimates and standard error of specific effect modifier like for example “Biochar_app_rate”. So when I run this model I get results for all these effect modifiers. Where “metrics4” is the dependent variable I am interested in (there are 8 dependent variables). + soil_sample_depth_max + country + annual_temp, Manure_app_rate + continent + soil_texture + soil_sample_depth_min Rma.mv(lnrr, v, random = ~ 1 | publication_title / unique_id, mods = ~ duration_exp +įeedstock_rename + temp_group + Biochar_app_rate + fertilizer_app_rate + I am running a multilevel model for the meta-analysis using the following code: For instance, we may extract only the coefficient estimates by subsetting our matrix: Now, we can apply any matrix manipulation to our matrix of coefficients that we want. The previous R code saved the coefficient estimates, standard errors, t-values, and p-values in a typical matrix format. Let’s therefore convert the summary output of our model into a data matrix: ![]() However, the coefficient values are not stored in a handy format. The previous output of the RStudio console shows all the estimates we need. # Residual standard error: 1.011 on 994 degrees of freedom , data ) ) # Estimate model # Call: # lm(formula = y ~. First, we have to estimate our statistical model using the lm and summary functions: In this Example, I’ll illustrate how to estimate and save the regression coefficients of a linear model in R. The remaining variables x1-x5 are the predictors.Įxample: Extracting Coefficients of Linear Model The first variable y is the outcome variable. The previously shown RStudio console output shows the structure of our example data – It’s a data frame consisting of six numeric columns. Set.seed(87634) # Create random example data seed ( 87634 ) # Create random example data ![]()
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