temp_17mar2024.qmd

---
title: "R Model"
format: html
editor: visual
---

```{r}
library(nlme)
library(lme4)
library(readr)
library(Matrix)
library(nlme)
library(car)
library(ggplot2)

BMI_IOS_SCD_Asthma <- read_csv("BMI_IOS_SCD_Asthma.csv")
```

```{r}
bmi_data=BMI_IOS_SCD_Asthma
```

```{r}
head(bmi_data)
```

```{r}
colnames(bmi_data) <- c("Group", "Subject_ID", "Observation_number", "Hydroxyurea", "Asthma", "ICS", "LABA", "Gender", "Age_months", "Height_cm", "Weight_Kg", "BMI", "R5Hz_PP", "R20Hz_PP", "X5Hz_PP", "Fres_PP")
```

```{r}
bmi_data_clean = na.omit(bmi_data)
```

```{r}

?lme()
model_lme_clean <- lme(cbind(R5Hz_PP, R20Hz_PP, X5Hz_PP, Fres_PP) ~ BMI + Asthma + ICS + LABA + Gender + Age_months + Height_cm + Weight_Kg, 
                 random = list(Subject_ID = pdIdent(~1)), 
                 data = bmi_data_clean, 
                 method = "REML")
```

```{r}

model_lmer_clean <- lmer(R5Hz_PP + R20Hz_PP + X5Hz_PP + Fres_PP ~ BMI + Asthma + ICS + LABA + Gender + Age_months + Height_cm + Weight_Kg + (1 | Subject_ID), 
                   data = bmi_data_clean)
```

```{r}

AIC_lme <- AIC(model_lme_clean)
AIC_lmer <- AIC(model_lmer_clean)


cat("AIC for lme model:", AIC_lme, "\n")
cat("AIC for lmer model:", AIC_lmer, "\n")

if (AIC_lme < AIC_lmer) {
  final_model <- model_lme_clean
  cat("Final model selected: lme\n")
} else {
  final_model <- model_lmer_clean
  cat("Final model selected: lmer\n")
}


summary(final_model)

```

```{r}
residuals_clean <- resid(model_lme_clean)
```

```{r}

plot(predict(model_lme_clean), residuals_clean, xlab = "Fitted Values", ylab = "Residuals")
abline(h = 0, col = "red")  # Add horizontal line at y = 0
title("Residuals vs. Fitted Values")
```

```{r}
hist(residuals_clean, main = "Histogram of Residuals")
# Q-Q plot
qqPlot(residuals_clean, main = "Q-Q Plot of Residuals")
```

```{r}

shapiro.test(residuals(model_lme_clean))

qqnorm(residuals(model_lme_clean))
qqline(residuals(model_lme_clean))


```

```{r}

fitted_values <- fitted(model_lme_clean)
residuals <- residuals(model_lme_clean)


plot(fitted_values, residuals, xlab = "Fitted values", ylab = "Residuals",
     main = "Residuals vs Fitted Values Plot")
abline(h = 0, col = "red")  # Add a horizontal line at y = 0 for reference
```