search for: indep1

...dom = ~PDSI|Abbr, data = data.sub, method = "ML") #Get the coefficients for the fixed effects summary(F)$coefficients$fixed THE OUTCOME: > i.levels<-c("Tall","Short","Mixed","NoType") > summary(F)$coefficients$fixed (Intercept) indep1 indep2 PDSI PDSI2 indep1:PDSI 115.20850196 2.13074177 -18.64650516 2.32042307 -0.46510460 0.09965080 indep2:PDSI indep1:PDSI2 indep2:PDSI2 0.90607575 0.01106839 -0.28827352 Other order: > i.levels<-c("Mixed","Short","Tall&qu...

...ng to run a panel regression where I have a matrix of observations and a matrix of independant variables - examples would trying to predict countries's GDP with their data on education, FDI, tax rates, over time. For the purpose of simplicity, my data would be: dep = matrix(rnorm(50),ncol=5) indep1 = matrix(rnorm(50),ncol=5) indep2 = matrix(rnorm(50),ncol=5) >From what I could find, the lme{nlme} function would be the function. However, after I installed the package and I type in: > lme(dep~indep1, indep2) Error in model.frame.default(formula = ~indep1 + dep, data = c(-0.6366592986926...

Dear subscribers, I am looking for a function which would allow me to model the dependent variable as the number of successes in a series of Bernoulli trials. My data looks like this ID TRIALS SUCCESSESS INDEP1 INDEP2 INDEP3 1 4444 0 0.273 0.055 0.156 2 98170 74 0.123 0.456 0.789 3 145486 30 0.124 0.235 0.007 4 147149 49 0.888 0.357 0.321 5 60585 11 0.484 0.235 0....

...$two_way_anova <- renderText({ req(data()) "Two-way ANOVA with interaction" }) # Build ANOVA model with two-way interaction interaction_model <- reactive({ cols <- selected_columns() req(cols) data <- data() data$dep <- cols$dependent data$indep1 <- cols$independent1 data$indep2 <- cols$independent2 data$rand <- cols$random lmer(dep ~ indep1 * indep2 + (1|rand), data = data) }) # Run two-way ANOVA model with interaction output$model_summary <- renderPrint({ req(interaction_model()) Anova(interaction_mo...