actor-classification/SEM-Multivariable.R at main · RJain12/actor-classification · GitHub

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coded_renamed_columns_data <- na_renamed_columns_data

coded_renamed_columns_data[, 3] <- ifelse(coded_renamed_columns_data[, 3] == "Male", 0, 1)

# Replace values in column index 3 (assuming it's the fourth column)
coded_renamed_columns_data[, 4] <- ifelse(
  coded_renamed_columns_data[, 4] == "In high school", 1,
  ifelse(coded_renamed_columns_data[, 4] == "In college/undergraduate", 2,
         ifelse(coded_renamed_columns_data[, 4] == "In graduate school", 3,
                ifelse(coded_renamed_columns_data[, 4] == "In middle school", 0, 4)
         )
  )
)

coded_renamed_columns_data[, 5] <- ifelse(
  coded_renamed_columns_data[, 5] == "Africa", 0,
  ifelse(coded_renamed_columns_data[, 5] == "Asia", 1,
         ifelse(coded_renamed_columns_data[, 5] == "Europe", 2,
                ifelse(coded_renamed_columns_data[, 5] == "North America", 3,
                       ifelse(coded_renamed_columns_data[, 5] == "Oceania", 4,
                              ifelse(coded_renamed_columns_data[, 5] == "South America", 5, NA)
                       )
                )
         )
  )
)

coded_renamed_columns_data[, 6] <- ifelse(
  coded_renamed_columns_data[, 6] == "Frequent user (uses Discord 5-7 days/week)", 0,
  ifelse(coded_renamed_columns_data[, 6] == "Novice (uses Discord 1-2 days/week)", 1,
         ifelse(coded_renamed_columns_data[, 6] == "Proficient user (uses Discord 2-4 days/week)", 2,
                ifelse(coded_renamed_columns_data[, 6] == "Never used Discord.com", 3,
                       ifelse(coded_renamed_columns_data[, 6] == "Oceania", 4,
                              ifelse(coded_renamed_columns_data[, 6] == "South America", 5, NA)
                       )
                )
         )

  )
)

count_tally_matrix <- gender_matrix
data <- data.frame(
  DependentVariable = count_tally_matrix[, 2],
  Age = coded_renamed_columns_data[, 3],
  Gender = coded_renamed_columns_data[, 4],
  EducationalBackground = coded_renamed_columns_data[, 5],
  Continent = coded_renamed_columns_data[, 6]
)

# Fit the multiple regression model
model <- lm(DependentVariable ~ Age + Gender + EducationalBackground + Continent, data)

# View the summary of the regression model
summary(model)