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added possibility to add filename of result
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#!/bin/bash | ||
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cd eln_prod | ||
docker compose up |
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Sys.setenv(RUN_MODE = "SERVER") | ||
library(bs) | ||
app <- bs::app() | ||
shiny::shinyApp(app$ui, app$server) |
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Sys.setenv(RUN_MODE = "BROWSER") | ||
library(bs) | ||
app <- bs::app() | ||
shiny::shinyApp(app$ui, app$server) |
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library(gamm4) | ||
library(mgcv) | ||
library(multcomp) | ||
library(emmeans) | ||
library(lme4) | ||
library(lmerTest) | ||
df <- CO2 | ||
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# ANOVA | ||
# Linear Model | ||
lm <- lm(uptake ~ Treatment, data = df) | ||
summary(aov(lm)) | ||
# Generalized Linear Model | ||
glm <- glm(uptake ~ Treatment, data = df) | ||
anova(lm) | ||
anova(glm) | ||
# Mixed Linear Model | ||
lmm <- lmer(uptake ~ Treatment + (1 | Type), data = df) | ||
anova(lmm) | ||
# GAM Model | ||
gam_model <- gam(uptake ~ s(conc, k = 5), data = df) | ||
summary(gam_model) | ||
plot(gam_model, residuals = TRUE, pch = 16, rug = TRUE) | ||
# Fit a GAMM with a smooth term for conc and a random effect for Type | ||
gamm_model <- gamm4(uptake ~ s(conc, k = 5), random = ~(1 | Type), data = df) | ||
summary(gamm_model$gam) | ||
summary(gamm_model$mer) | ||
# Fit a GAM with a smooth term for conc and a categorical predictor | ||
gam_model <- gam(uptake ~ s(conc, k = 5) + Treatment, data = df) | ||
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# POSTHOC TESTS | ||
emmeans_result <- emmeans(glm, pairwise ~ Treatment) | ||
summary(emmeans_result) | ||
glht_result <- glht(glm, linfct = mcp(Treatment = "Tukey")) | ||
summary(glht_result) | ||
glht_result <- glht(lmm, linfct = mcp(Treatment = "Tukey")) | ||
summary(glht_result) | ||
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# Alternative for Continuous Predictor (e.g., conc) | ||
lm_cont <- lm(uptake ~ conc, data = df) | ||
summary(lm_cont) | ||
glm_cont <- glm(uptake ~ conc, data = df) | ||
summary(glm_cont) | ||
lmm_cont <- lmer(uptake ~ conc + (1 | Type), data = df) | ||
summary(lmm_cont) | ||
# Post hoc comparisons for Treatment levels with gam | ||
emmeans_result <- emmeans(gam_model, pairwise ~ Treatment) | ||
summary(emmeans_result) | ||
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