Hello R Community, Subject: Bayes Factor A Bayesian ANOVA of the form: competitionBayesOut <- anovaBF(biomass ~ clipping, data = competition) Returns the following Error message: Error in (function (classes, fdef, mtable) : unable to find an inherited method for function ‘compare’ for signature ‘"BFlinearModel", "missing", "tbl_df"’
My guess the problem is in the ‘class’, which is: [1] “tbl_df” “tbl” “data.frame” The data was imported via the ‘readr’ package through R Studio, and then saved as a RData file. My code is below, and the data is attached as a text file. Thanks for your assistance. Best regards, James # Plots for Interpreting One-Way ANOVA library(digest) library(DT) datatable(competition) # Characterize the data. class(competition) str(competition) competition$clipping <- as.factor(competition$clipping) competition$biomass <- as.numeric(competition$biomass) str(competition) # tapply(competition$biomass, competition$clipping, mean) tapply(competition$biomass, competition$clipping, sd) # Bayesian Procedure for ANOVA # Calculate Bayes Factors library(BayesFactor) competitionBayesOut <- anovaBF(biomass ~ clipping, data = competition) # Run mcmc iterations mcmcOut2 <- posterior(competitionBayesOut, iterations = 10000) # boxplot of the posteriors for the groups boxplot(as.matrix(mcmcOut2[,2:6])) # Show the HDIs summary(mcmcOut2) # Calculate the Bayes Factor competitionBayesOut # Pairwise "post hoc" tests library(rjags) library(BEST) # competitionare 'r5' vs. 'control' plot(BESTmcmc(competition[competition$clpping=="r5",2], competition[competition$clipping=="control",2])) # plot(BESTmcmc(competition[competition$clpping=="r10",2], competition[competition$clipping=="control",2])) # competitionare 'n10' vs. 'control' plot(BESTmcmc(competition[competition$clipping=="n10",2], competition[competition$clipping=="control",2])) # competitionare 'n50' vs. 'control' plot(BESTmcmc(competition[competition$clipping=="n50",2], competition[competition$clipping=="control",2]))
clipping biomass n25 551 n25 457 n25 450 n25 731 n25 499 n25 632 n50 595 n50 580 n50 508 n50 583 n50 633 n50 517 r5 639 r5 615 r5 511 r5 573 r5 648 r5 677 control 417 control 449 control 517 control 438 control 415 control 555 r10 563 r10 631 r10 522 r10 613 r10 656 r10 679
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