eholk · November 23, 2025 02:09
diff --git a/analyze-data.R b/analyze-data.R
 # Analysis script for vitamin experiment
 #
 # This script analyzes the combined vitamin experiment data to determine if
 # taking a multivitamin is associated with weight gain.
 #
 # The analysis includes:
 # 1. Linear regression models for vitamin vs no-vitamin phases
 # 2. Statistical comparison of slopes and confidence intervals
 # 3. Visualization of the data and fitted models
 #
 # Decision criteria: If the confidence intervals for the slopes do not overlap,
 # and the vitamin slope is significantly greater than zero, then vitamins are
 # associated with weight gain.
 #
 # See: https://manifold.markets/theincredibleholk/does-taking-a-multivitamin-cause-me

 # Install and load required packages
 if (!require(ggplot2)) {
    install.packages("ggplot2")
    library(ggplot2)
 }

 if (!require(dplyr)) {
    install.packages("dplyr")
    library(dplyr)
 }

 # Load the combined data
 cat("=== Loading Combined Data ===\n")
 all_data <- read.csv("vitamin_experiment_data.csv", stringsAsFactors = FALSE)

 # Convert Date back to Date type
 all_data$Date <- as.Date(all_data$Date)

 cat("Loaded", nrow(all_data), "total observations\n")
 cat("Date range:", as.character(min(all_data$Date)), "to", as.character(max(all_data$Date)), "\n")

 # Display summary
 cat("\nObservations by phase:\n")
 print(table(all_data$Phase))

 # === PREPARE DATA FOR ANALYSIS ===

 # Separate into vitamin and no-vitamin phases
 # Filter to only rows with valid delta data for modeling
 vitamin_data <- all_data[all_data$PhaseType == "Vitamin" & !is.na(all_data$Delta), ]
 no_vitamin_data <- all_data[all_data$PhaseType == "NoVitamin" & !is.na(all_data$Delta), ]

 cat("\n=== Analysis Data Summary ===\n")
 cat("Vitamin phase observations:", nrow(vitamin_data), "\n")
 cat("No vitamin phase observations:", nrow(no_vitamin_data), "\n")

 # Display first few rows
 cat("\n=== Vitamin Phase Data (first 6 rows) ===\n")
 print(head(vitamin_data))

 cat("\n=== No Vitamin Phase Data (first 6 rows) ===\n")
 print(head(no_vitamin_data))

 # === LINEAR MODEL ANALYSIS ===

 cat("\n=== Linear Model Analysis ===\n")

 # Model for vitamin phase: Delta ~ Day
 vitamin_model <- lm(Delta ~ Day, data = vitamin_data)
 cat("\nVitamin Phase Model Summary:\n")
 print(summary(vitamin_model))

 # Model for no vitamin phase: Delta ~ Day
 no_vitamin_model <- lm(Delta ~ Day, data = no_vitamin_data)
 cat("\nNo Vitamin Phase Model Summary:\n")
 print(summary(no_vitamin_model))

 # Extract coefficients and confidence intervals
 vitamin_coef <- coef(vitamin_model)["Day"]
 vitamin_ci <- confint(vitamin_model)["Day", ]
 no_vitamin_coef <- coef(no_vitamin_model)["Day"]
 no_vitamin_ci <- confint(no_vitamin_model)["Day", ]

 cat("\n=== Coefficient Analysis ===\n")
 cat("Vitamin phase - Day coefficient:", round(vitamin_coef, 4), "\n")
 cat("Vitamin phase - 95% CI: [", round(vitamin_ci[1], 4), ",", round(vitamin_ci[2], 4), "]\n")
 cat("No vitamin phase - Day coefficient:", round(no_vitamin_coef, 4), "\n")
 cat("No vitamin phase - 95% CI: [", round(no_vitamin_ci[1], 4), ",", round(no_vitamin_ci[2], 4), "]\n")

 # === STATISTICAL DECISION ===

 cat("\n=== Statistical Decision ===\n")

 # Check if vitamin coefficient CI is entirely greater than zero (absolute weight gain effect)
 vitamin_causes_gain <- vitamin_ci[1] > 0

 # Check if vitamin coefficient CI is entirely greater than no-vitamin CI (relative weight gain effect)
 vitamin_causes_relative_gain <- vitamin_ci[1] > no_vitamin_ci[2]

 # Check if confidence intervals don't overlap (already captures significant difference)
 ci_no_overlap <- (vitamin_ci[2] < no_vitamin_ci[1]) || (no_vitamin_ci[2] < vitamin_ci[1])

 cat("Vitamin CI entirely > 0 (absolute weight gain):", vitamin_causes_gain, "\n")
 cat("Vitamin CI entirely > No-vitamin CI (relative weight gain):", vitamin_causes_relative_gain, "\n")
 cat("Confidence intervals do not overlap:", ci_no_overlap, "\n")

 if (vitamin_causes_gain && vitamin_causes_relative_gain && ci_no_overlap) {
    cat("\n*** CONCLUSION: Vitamins cause weight gain! ***\n")
    cat("The vitamin phase shows a statistically significant positive weight delta trend\n")
    cat("that is both greater than zero and greater than the no-vitamin phase effect.\n")
 } else {
    cat("\n*** CONCLUSION: No significant weight gain effect detected. ***\n")
    if (!vitamin_causes_gain) {
        cat("The vitamin coefficient confidence interval includes zero or negative values,\n")
        cat("indicating no significant absolute weight gain effect.\n")
    }
    if (!vitamin_causes_relative_gain) {
        cat("The vitamin coefficient confidence interval is not entirely greater than\n")
        cat("the no-vitamin confidence interval, indicating no clear relative weight gain effect.\n")
    }
    if (!ci_no_overlap) {
        cat("The confidence intervals for vitamin and no-vitamin phases overlap,\n")
        cat("indicating no significant difference between the two phases.\n")
    }
 }

 # === PLOTTING ===

 cat("\n=== Creating Plots ===\n")

 # Create prediction data for smooth lines and confidence intervals
 day_range <- range(c(vitamin_data$Day, no_vitamin_data$Day))
 pred_days <- seq(day_range[1], day_range[2], length.out = 100)

 # Generate predictions with confidence intervals for both models
 vitamin_pred <- predict(vitamin_model,
    newdata = data.frame(Day = pred_days),
    interval = "confidence", level = 0.95
 )
 no_vitamin_pred <- predict(no_vitamin_model,
    newdata = data.frame(Day = pred_days),
    interval = "confidence", level = 0.95
 )

 # Create prediction data frames
 vitamin_pred_df <- data.frame(
    Day = pred_days,
    fit = vitamin_pred[, "fit"],
    lwr = vitamin_pred[, "lwr"],
    upr = vitamin_pred[, "upr"],
    PhaseType = "Vitamin"
 )

 no_vitamin_pred_df <- data.frame(
    Day = pred_days,
    fit = no_vitamin_pred[, "fit"],
    lwr = no_vitamin_pred[, "lwr"],
    upr = no_vitamin_pred[, "upr"],
    PhaseType = "NoVitamin"
 )

 # Combine prediction data
 pred_data <- rbind(vitamin_pred_df, no_vitamin_pred_df)

 # Create the plot
 p <- ggplot() +
    # Add confidence interval ribbons
    geom_ribbon(
        data = pred_data,
        aes(x = Day, ymin = lwr, ymax = upr, fill = PhaseType),
        alpha = 0.3
    ) +

    # Add fitted lines
    geom_line(
        data = pred_data,
        aes(x = Day, y = fit, color = PhaseType),
        linewidth = 1.2
    ) +

    # Add data points
    geom_point(
        data = vitamin_data,
        aes(x = Day, y = Delta, color = "Vitamin"),
        size = 2, alpha = 0.7
    ) +
    geom_point(
        data = no_vitamin_data,
        aes(x = Day, y = Delta, color = "NoVitamin"),
        size = 2, alpha = 0.7
    ) +

    # Customize colors
    scale_color_manual(
        values = c("Vitamin" = "#E74C3C", "NoVitamin" = "#3498DB"),
        labels = c("Vitamin", "No Vitamin")
    ) +
    scale_fill_manual(
        values = c("Vitamin" = "#E74C3C", "NoVitamin" = "#3498DB"),
        labels = c("Vitamin", "No Vitamin")
    ) +

    # Add labels and title
    labs(
        title = "Vitamin Experiment: Weight Delta vs Day",
        subtitle = "Linear regression with 95% confidence intervals",
        x = "Day (within phase)",
        y = "Weight Delta (lbs)",
        color = "Phase Type",
        fill = "Phase Type"
    ) +

    # Add a horizontal line at y = 0 for reference
    geom_hline(yintercept = 0, linetype = "dashed", color = "gray50", alpha = 0.7) +

    # Theme with white background
    theme_bw() +
    theme(
        plot.title = element_text(size = 14, face = "bold"),
        plot.subtitle = element_text(size = 12),
        legend.position = "bottom",
        panel.grid.minor = element_blank()
    )

 # Display the plot
 print(p)

 # Save the plot
 ggsave("vitamin_experiment_plot.png", plot = p, width = 10, height = 6, dpi = 300)
 cat("Plot saved as 'vitamin_experiment_plot.png'\n")

 cat("\n=== Analysis Complete ===\n")
diff --git a/vitamin_experiment_data.csv b/vitamin_experiment_data.csv
	# Analysis script for vitamin experiment
	#
	# This script analyzes the combined vitamin experiment data to determine if
	# taking a multivitamin is associated with weight gain.
	#
	# The analysis includes:
	# 1. Linear regression models for vitamin vs no-vitamin phases
	# 2. Statistical comparison of slopes and confidence intervals
	# 3. Visualization of the data and fitted models
	#
	# Decision criteria: If the confidence intervals for the slopes do not overlap,
	# and the vitamin slope is significantly greater than zero, then vitamins are
	# associated with weight gain.
	#
	# See: https://manifold.markets/theincredibleholk/does-taking-a-multivitamin-cause-me

	# Install and load required packages
	if (!require(ggplot2)) {
	install.packages("ggplot2")
	library(ggplot2)
	}

	if (!require(dplyr)) {
	install.packages("dplyr")
	library(dplyr)
	}

	# Load the combined data
	cat("=== Loading Combined Data ===\n")
	all_data <- read.csv("vitamin_experiment_data.csv", stringsAsFactors = FALSE)

	# Convert Date back to Date type
	all_data$Date <- as.Date(all_data$Date)

	cat("Loaded", nrow(all_data), "total observations\n")
	cat("Date range:", as.character(min(all_data$Date)), "to", as.character(max(all_data$Date)), "\n")

	# Display summary
	cat("\nObservations by phase:\n")
	print(table(all_data$Phase))

	# === PREPARE DATA FOR ANALYSIS ===

	# Separate into vitamin and no-vitamin phases
	# Filter to only rows with valid delta data for modeling
	vitamin_data <- all_data[all_data$PhaseType == "Vitamin" & !is.na(all_data$Delta), ]
	no_vitamin_data <- all_data[all_data$PhaseType == "NoVitamin" & !is.na(all_data$Delta), ]

	cat("\n=== Analysis Data Summary ===\n")
	cat("Vitamin phase observations:", nrow(vitamin_data), "\n")
	cat("No vitamin phase observations:", nrow(no_vitamin_data), "\n")

	# Display first few rows
	cat("\n=== Vitamin Phase Data (first 6 rows) ===\n")
	print(head(vitamin_data))

	cat("\n=== No Vitamin Phase Data (first 6 rows) ===\n")
	print(head(no_vitamin_data))

	# === LINEAR MODEL ANALYSIS ===

	cat("\n=== Linear Model Analysis ===\n")

	# Model for vitamin phase: Delta ~ Day
	vitamin_model <- lm(Delta ~ Day, data = vitamin_data)
	cat("\nVitamin Phase Model Summary:\n")
	print(summary(vitamin_model))

	# Model for no vitamin phase: Delta ~ Day
	no_vitamin_model <- lm(Delta ~ Day, data = no_vitamin_data)
	cat("\nNo Vitamin Phase Model Summary:\n")
	print(summary(no_vitamin_model))

	# Extract coefficients and confidence intervals
	vitamin_coef <- coef(vitamin_model)["Day"]
	vitamin_ci <- confint(vitamin_model)["Day", ]
	no_vitamin_coef <- coef(no_vitamin_model)["Day"]
	no_vitamin_ci <- confint(no_vitamin_model)["Day", ]

	cat("\n=== Coefficient Analysis ===\n")
	cat("Vitamin phase - Day coefficient:", round(vitamin_coef, 4), "\n")
	cat("Vitamin phase - 95% CI: [", round(vitamin_ci[1], 4), ",", round(vitamin_ci[2], 4), "]\n")
	cat("No vitamin phase - Day coefficient:", round(no_vitamin_coef, 4), "\n")
	cat("No vitamin phase - 95% CI: [", round(no_vitamin_ci[1], 4), ",", round(no_vitamin_ci[2], 4), "]\n")

	# === STATISTICAL DECISION ===

	cat("\n=== Statistical Decision ===\n")

	# Check if vitamin coefficient CI is entirely greater than zero (absolute weight gain effect)
	vitamin_causes_gain <- vitamin_ci[1] > 0

	# Check if vitamin coefficient CI is entirely greater than no-vitamin CI (relative weight gain effect)
	vitamin_causes_relative_gain <- vitamin_ci[1] > no_vitamin_ci[2]

	# Check if confidence intervals don't overlap (already captures significant difference)
	ci_no_overlap <- (vitamin_ci[2] < no_vitamin_ci[1]) \|\| (no_vitamin_ci[2] < vitamin_ci[1])

	cat("Vitamin CI entirely > 0 (absolute weight gain):", vitamin_causes_gain, "\n")
	cat("Vitamin CI entirely > No-vitamin CI (relative weight gain):", vitamin_causes_relative_gain, "\n")
	cat("Confidence intervals do not overlap:", ci_no_overlap, "\n")

	if (vitamin_causes_gain && vitamin_causes_relative_gain && ci_no_overlap) {
	cat("\n* CONCLUSION: Vitamins cause weight gain! *\n")
	cat("The vitamin phase shows a statistically significant positive weight delta trend\n")
	cat("that is both greater than zero and greater than the no-vitamin phase effect.\n")
	} else {
	cat("\n* CONCLUSION: No significant weight gain effect detected. *\n")
	if (!vitamin_causes_gain) {
	cat("The vitamin coefficient confidence interval includes zero or negative values,\n")
	cat("indicating no significant absolute weight gain effect.\n")
	}
	if (!vitamin_causes_relative_gain) {
	cat("The vitamin coefficient confidence interval is not entirely greater than\n")
	cat("the no-vitamin confidence interval, indicating no clear relative weight gain effect.\n")
	}
	if (!ci_no_overlap) {
	cat("The confidence intervals for vitamin and no-vitamin phases overlap,\n")
	cat("indicating no significant difference between the two phases.\n")
	}
	}

	# === PLOTTING ===

	cat("\n=== Creating Plots ===\n")

	# Create prediction data for smooth lines and confidence intervals
	day_range <- range(c(vitamin_data$Day, no_vitamin_data$Day))
	pred_days <- seq(day_range[1], day_range[2], length.out = 100)

	# Generate predictions with confidence intervals for both models
	vitamin_pred <- predict(vitamin_model,
	newdata = data.frame(Day = pred_days),
	interval = "confidence", level = 0.95
	)
	no_vitamin_pred <- predict(no_vitamin_model,
	newdata = data.frame(Day = pred_days),
	interval = "confidence", level = 0.95
	)

	# Create prediction data frames
	vitamin_pred_df <- data.frame(
	Day = pred_days,
	fit = vitamin_pred[, "fit"],
	lwr = vitamin_pred[, "lwr"],
	upr = vitamin_pred[, "upr"],
	PhaseType = "Vitamin"
	)

	no_vitamin_pred_df <- data.frame(
	Day = pred_days,
	fit = no_vitamin_pred[, "fit"],
	lwr = no_vitamin_pred[, "lwr"],
	upr = no_vitamin_pred[, "upr"],
	PhaseType = "NoVitamin"
	)

	# Combine prediction data
	pred_data <- rbind(vitamin_pred_df, no_vitamin_pred_df)

	# Create the plot
	p <- ggplot() +
	# Add confidence interval ribbons
	geom_ribbon(
	data = pred_data,
	aes(x = Day, ymin = lwr, ymax = upr, fill = PhaseType),
	alpha = 0.3
	) +

	# Add fitted lines
	geom_line(
	data = pred_data,
	aes(x = Day, y = fit, color = PhaseType),
	linewidth = 1.2
	) +

	# Add data points
	geom_point(
	data = vitamin_data,
	aes(x = Day, y = Delta, color = "Vitamin"),
	size = 2, alpha = 0.7
	) +
	geom_point(
	data = no_vitamin_data,
	aes(x = Day, y = Delta, color = "NoVitamin"),
	size = 2, alpha = 0.7
	) +

	# Customize colors
	scale_color_manual(
	values = c("Vitamin" = "#E74C3C", "NoVitamin" = "#3498DB"),
	labels = c("Vitamin", "No Vitamin")
	) +
	scale_fill_manual(
	values = c("Vitamin" = "#E74C3C", "NoVitamin" = "#3498DB"),
	labels = c("Vitamin", "No Vitamin")
	) +

	# Add labels and title
	labs(
	title = "Vitamin Experiment: Weight Delta vs Day",
	subtitle = "Linear regression with 95% confidence intervals",
	x = "Day (within phase)",
	y = "Weight Delta (lbs)",
	color = "Phase Type",
	fill = "Phase Type"
	) +

	# Add a horizontal line at y = 0 for reference
	geom_hline(yintercept = 0, linetype = "dashed", color = "gray50", alpha = 0.7) +

	# Theme with white background
	theme_bw() +
	theme(
	plot.title = element_text(size = 14, face = "bold"),
	plot.subtitle = element_text(size = 12),
	legend.position = "bottom",
	panel.grid.minor = element_blank()
	)

	# Display the plot
	print(p)

	# Save the plot
	ggsave("vitamin_experiment_plot.png", plot = p, width = 10, height = 6, dpi = 300)
	cat("Plot saved as 'vitamin_experiment_plot.png'\n")

	cat("\n=== Analysis Complete ===\n")
Phase	PhaseType	PhaseNumber	Day	Date	DaySinceStart	Delta	DeltaSinceStart	Took.Vitamin	Travel	Notes
Vitamin-1	Vitamin	1	0	2025-04-25	0	0	0	1	NA	NA
Vitamin-1	Vitamin	1	1	2025-04-26	1	0.1	0.0999999999999943	1	NA	NA
Vitamin-1	Vitamin	1	2	2025-04-27	2	2.8	2.80000000000001	1	NA	NA
Vitamin-1	Vitamin	1	3	2025-04-28	3	1.9	1.90000000000001	1	NA	NA
Vitamin-1	Vitamin	1	4	2025-04-29	4	2	2	1	NA	NA
Vitamin-1	Vitamin	1	5	2025-04-30	5	2.5	2.5	1	NA	NA
Vitamin-1	Vitamin	1	6	2025-05-01	6	2.4	2.40000000000001	1	NA	NA
Vitamin-1	Vitamin	1	7	2025-05-02	7	1.4	1.40000000000001	1	NA	NA
Vitamin-1	Vitamin	1	8	2025-05-03	8	2.1	2.09999999999999	1	NA	NA
Vitamin-1	Vitamin	1	9	2025-05-04	9	1.7	1.70000000000002	1	NA	NA
Vitamin-1	Vitamin	1	10	2025-05-05	10	0.8	0.800000000000011	1	NA	NA
Vitamin-1	Vitamin	1	11	2025-05-06	11	1.6	1.59999999999999	1	NA	NA
Vitamin-1	Vitamin	1	12	2025-05-07	12	2.4	2.40000000000001	1	NA	NA
Vitamin-1	Vitamin	1	13	2025-05-08	13	2.8	2.80000000000001	1	NA	NA
Vitamin-1	Vitamin	1	14	2025-05-09	14	0.5	0.5	1	NA	NA
Vitamin-1	Vitamin	1	15	2025-05-10	15	NA	NA	1	1	NA
Vitamin-1	Vitamin	1	16	2025-05-11	16	NA	NA	1	1	NA
Vitamin-1	Vitamin	1	17	2025-05-12	17	NA	NA	1	1	NA
Vitamin-1	Vitamin	1	18	2025-05-13	18	NA	NA	1	1	NA
Vitamin-1	Vitamin	1	19	2025-05-14	19	NA	NA	1	1	NA
Vitamin-1	Vitamin	1	20	2025-05-15	20	NA	NA	1	1	NA
Vitamin-1	Vitamin	1	21	2025-05-16	21	NA	NA	1	1	NA
Vitamin-1	Vitamin	1	22	2025-05-17	22	NA	NA	1	1	NA
Vitamin-1	Vitamin	1	23	2025-05-18	23	NA	NA	1	1	NA
Vitamin-1	Vitamin	1	24	2025-05-19	24	NA	NA	1	1	NA
Vitamin-1	Vitamin	1	25	2025-05-20	25	NA	NA	1	1	NA
Vitamin-1	Vitamin	1	26	2025-05-21	26	-1.7	-1.69999999999999	1	NA	NA
Vitamin-1	Vitamin	1	27	2025-05-22	27	0.9	0.900000000000006	1	NA	NA
Vitamin-1	Vitamin	1	28	2025-05-23	28	0.1	0.0999999999999943	1	NA	NA
Vitamin-1	Vitamin	1	29	2025-05-24	29	1.1	1.09999999999999	1	NA	NA
Vitamin-1	Vitamin	1	30	2025-05-25	30	2.6	2.59999999999999	0	NA	NA
NoVitamin-1	NoVitamin	1	0	2025-05-25	30	0	2.59999999999999	0	NA	NA
NoVitamin-1	NoVitamin	1	1	2025-05-26	31	0.6	3.20000000000002	0	NA	NA
NoVitamin-1	NoVitamin	1	2	2025-05-27	32	0.8	3.40000000000001	0	NA	NA
NoVitamin-1	NoVitamin	1	3	2025-05-28	33	2.7	5.30000000000001	0	NA	NA
NoVitamin-1	NoVitamin	1	4	2025-05-29	34	1.6	4.20000000000002	0	NA	NA
NoVitamin-1	NoVitamin	1	5	2025-05-30	35	2.8	5.40000000000001	0	NA	NA
NoVitamin-1	NoVitamin	1	6	2025-05-31	36	3.3	5.90000000000001	0	NA	NA
NoVitamin-1	NoVitamin	1	7	2025-06-01	37	1.9	4.5	0	NA	NA
NoVitamin-1	NoVitamin	1	8	2025-06-02	38	2	4.59999999999999	0	NA	NA
NoVitamin-1	NoVitamin	1	9	2025-06-03	39	1.4	4	0	NA	NA
NoVitamin-1	NoVitamin	1	10	2025-06-04	40	3.6	6.20000000000002	0	NA	NA
NoVitamin-1	NoVitamin	1	11	2025-06-05	41	0.8	3.40000000000001	0	NA	NA
NoVitamin-1	NoVitamin	1	12	2025-06-06	42	1.2	3.80000000000001	0	NA	NA
NoVitamin-1	NoVitamin	1	13	2025-06-07	43	2.5	5.09999999999999	0	NA	NA
NoVitamin-1	NoVitamin	1	14	2025-06-08	44	1.5	4.09999999999999	0	NA	NA
NoVitamin-1	NoVitamin	1	15	2025-06-09	45	2.7	5.30000000000001	0	NA	NA
NoVitamin-1	NoVitamin	1	16	2025-06-10	46	1.4	4	0	NA	NA
NoVitamin-1	NoVitamin	1	17	2025-06-11	47	0	2.59999999999999	0	NA	NA
NoVitamin-1	NoVitamin	1	18	2025-06-12	48	0.3	2.90000000000001	0	NA	NA
NoVitamin-1	NoVitamin	1	19	2025-06-13	49	1.3	3.90000000000001	0	NA	NA
NoVitamin-1	NoVitamin	1	20	2025-06-14	50	0.1	2.70000000000002	0	NA	NA
NoVitamin-1	NoVitamin	1	21	2025-06-15	51	0.1	2.70000000000002	0	NA	NA
NoVitamin-1	NoVitamin	1	22	2025-06-16	52	0.6	3.20000000000002	0	NA	NA
NoVitamin-1	NoVitamin	1	23	2025-06-17	53	0.6	3.20000000000002	0	NA	NA
NoVitamin-1	NoVitamin	1	24	2025-06-18	54	1.8	4.40000000000001	0	NA	NA
NoVitamin-1	NoVitamin	1	25	2025-06-19	55	0.6	3.20000000000002	0	NA	NA
NoVitamin-1	NoVitamin	1	26	2025-06-20	56	2.5	5.09999999999999	0	NA	NA
NoVitamin-1	NoVitamin	1	27	2025-06-21	57	0.1	2.70000000000002	0	NA	NA
NoVitamin-1	NoVitamin	1	28	2025-06-22	58	2.5	5.09999999999999	0	NA	NA
NoVitamin-1	NoVitamin	1	29	2025-06-23	59	2.2	4.80000000000001	0	NA	NA
NoVitamin-1	NoVitamin	1	30	2025-06-24	60	2.1	4.70000000000002	0	NA	NA
Vitamin-2	Vitamin	2	0	2025-07-17	83	0	4.70000000000002	1	NA	Delayed start of Phase 2A due to travel
Vitamin-2	Vitamin	2	1	2025-07-18	84	0	4.70000000000002	1	NA
Vitamin-2	Vitamin	2	2	2025-07-19	85	-2.6	2.09999999999999	1	NA
Vitamin-2	Vitamin	2	3	2025-07-20	86	NA	NA	1	NA	Didn't weigh myself today
Vitamin-2	Vitamin	2	4	2025-07-21	87	0.5	5.20000000000002	1	NA
Vitamin-2	Vitamin	2	5	2025-07-22	88	1	5.70000000000002	1	NA
Vitamin-2	Vitamin	2	6	2025-07-23	89	NA	NA	1	NA	Didn't weigh myself today
Vitamin-2	Vitamin	2	7	2025-07-24	90	-0.1	4.59999999999999	1	NA
Vitamin-2	Vitamin	2	8	2025-07-25	91	-0.1	4.59999999999999	1	NA
Vitamin-2	Vitamin	2	9	2025-07-26	92	-0.3	4.40000000000001	0	NA	I can't remember if I took my vitamins today, so I left it as no.
Vitamin-2	Vitamin	2	10	2025-07-27	93	NA	NA	1	NA	Didn't weigh myself today
Vitamin-2	Vitamin	2	11	2025-07-28	94	0.2	4.90000000000001	1	NA
Vitamin-2	Vitamin	2	12	2025-07-29	95	0.2	4.90000000000001	1	NA
Vitamin-2	Vitamin	2	13	2025-07-30	96	0.1	4.80000000000001	1	NA
Vitamin-2	Vitamin	2	14	2025-07-31	97	1.4	6.09999999999999	1	NA
Vitamin-2	Vitamin	2	15	2025-08-01	98	-2.1	2.59999999999999	1	NA
Vitamin-2	Vitamin	2	16	2025-08-02	99	-0.6	4.09999999999999	1	NA
Vitamin-2	Vitamin	2	17	2025-08-03	100	0.5	5.20000000000002	1	NA
Vitamin-2	Vitamin	2	18	2025-08-04	101	0.6	5.30000000000001	1	NA
Vitamin-2	Vitamin	2	19	2025-08-05	102	-1.5	3.20000000000002	1	NA
Vitamin-2	Vitamin	2	20	2025-08-06	103	-1.1	3.59999999999999	1	NA
Vitamin-2	Vitamin	2	21	2025-08-07	104	-0.5	4.20000000000002	1	NA
Vitamin-2	Vitamin	2	22	2025-08-08	105	0.2	4.90000000000001	1	NA
Vitamin-2	Vitamin	2	23	2025-08-09	106	-0.2	4.5	1	NA
Vitamin-2	Vitamin	2	24	2025-08-10	107	1.4	6.09999999999999	1	NA
Vitamin-2	Vitamin	2	25	2025-08-11	108	0.6	5.30000000000001	1	NA
Vitamin-2	Vitamin	2	26	2025-08-12	109	-1	3.70000000000002	1	NA
Vitamin-2	Vitamin	2	27	2025-08-13	110	0.5	5.20000000000002	1	NA
Vitamin-2	Vitamin	2	28	2025-08-14	111	-0.3	4.40000000000001	1	NA
Vitamin-2	Vitamin	2	29	2025-08-15	112	-0.9	3.80000000000001	1	NA
Vitamin-2	Vitamin	2	30	2025-08-16	113	-1.5	3.20000000000002	0	NA
NoVitamin-2	NoVitamin	2	0	2025-08-16	113	0	3.20000000000002	0	NA
NoVitamin-2	NoVitamin	2	1	2025-08-17	114	NA	NA	0	NA	Didn't weight myself today.
NoVitamin-2	NoVitamin	2	2	2025-08-18	115	1.1	4.30000000000001	0	NA
NoVitamin-2	NoVitamin	2	3	2025-08-19	116	0.3	3.5	0	NA
NoVitamin-2	NoVitamin	2	4	2025-08-20	117	-1	2.20000000000002	0	NA
NoVitamin-2	NoVitamin	2	5	2025-08-21	118	-0.7	2.5	0	NA
NoVitamin-2	NoVitamin	2	6	2025-08-22	119	0.9	4.09999999999999	0	NA
NoVitamin-2	NoVitamin	2	7	2025-08-23	120	-1.2	2	0	NA
NoVitamin-2	NoVitamin	2	8	2025-08-24	121	-0.9	2.30000000000001	0	NA
NoVitamin-2	NoVitamin	2	9	2025-08-25	122	-1.4	1.80000000000001	0	NA
NoVitamin-2	NoVitamin	2	10	2025-08-26	123	-0.6	2.59999999999999	0	NA
NoVitamin-2	NoVitamin	2	11	2025-08-27	124	-1.1	2.09999999999999	0	NA
NoVitamin-2	NoVitamin	2	12	2025-08-28	125	-0.4	2.80000000000001	0	NA
NoVitamin-2	NoVitamin	2	13	2025-08-29	126	0.1	3.30000000000001	0	NA
NoVitamin-2	NoVitamin	2	14	2025-08-30	127	-1.9	1.30000000000001	0	NA
NoVitamin-2	NoVitamin	2	15	2025-08-31	128	-2.1	1.09999999999999	0	NA
NoVitamin-2	NoVitamin	2	16	2025-09-01	129	-1.3	1.90000000000001	0	NA
NoVitamin-2	NoVitamin	2	17	2025-09-02	130	NA	NA	0	1
NoVitamin-2	NoVitamin	2	18	2025-09-03	131	NA	NA	0	1
NoVitamin-2	NoVitamin	2	19	2025-09-04	132	NA	NA	0	1
NoVitamin-2	NoVitamin	2	20	2025-09-05	133	NA	NA	0	1
NoVitamin-2	NoVitamin	2	21	2025-09-06	134	NA	NA	0	1	Post-travel rest day
NoVitamin-2	NoVitamin	2	22	2025-09-07	135	NA	NA	0	1	Post-travel rest day
NoVitamin-2	NoVitamin	2	23	2025-09-08	136	-1.6	1.59999999999999	0	NA
NoVitamin-2	NoVitamin	2	24	2025-09-09	137	-1.9	1.30000000000001	0	NA
NoVitamin-2	NoVitamin	2	25	2025-09-10	138	-3.7	-0.5	0	NA
NoVitamin-2	NoVitamin	2	26	2025-09-11	139	-2.7	0.5	0	NA
NoVitamin-2	NoVitamin	2	27	2025-09-12	140	-3.4	-0.199999999999989	0	NA
NoVitamin-2	NoVitamin	2	28	2025-09-13	141	-2.9	0.300000000000011	0	NA
NoVitamin-2	NoVitamin	2	29	2025-09-14	142	-4	-0.799999999999983	0	NA
NoVitamin-2	NoVitamin	2	30	2025-09-15	143	-2.2	1	0	NA
Vitamin-3	Vitamin	3	0	2025-09-18	146	0	-0.799999999999983	1	NA	NA
Vitamin-3	Vitamin	3	1	2025-09-19	147	0.6	-0.199999999999989	1	NA	NA
Vitamin-3	Vitamin	3	2	2025-09-20	148	0.1	-0.699999999999989	1	NA	NA
Vitamin-3	Vitamin	3	3	2025-09-21	149	3.1	2.30000000000001	1	NA	NA
Vitamin-3	Vitamin	3	4	2025-09-22	150	3	2.20000000000002	1	NA	NA
Vitamin-3	Vitamin	3	5	2025-09-23	151	1.2	0.400000000000006	1	NA	NA
Vitamin-3	Vitamin	3	6	2025-09-24	152	0.3	-0.5	1	NA	NA
Vitamin-3	Vitamin	3	7	2025-09-25	153	-0.1	-0.900000000000006	1	NA	NA
Vitamin-3	Vitamin	3	8	2025-09-26	154	0.8	0	1	NA	NA
Vitamin-3	Vitamin	3	9	2025-09-27	155	0.6	-0.199999999999989	1	NA	NA
Vitamin-3	Vitamin	3	10	2025-09-28	156	1.8	1	1	NA	NA
Vitamin-3	Vitamin	3	11	2025-09-29	157	2.1	1.30000000000001	1	NA	NA
Vitamin-3	Vitamin	3	12	2025-09-30	158	1.7	0.900000000000006	1	NA	NA
Vitamin-3	Vitamin	3	13	2025-10-01	159	0.4	-0.400000000000006	0	NA	NA
Vitamin-3	Vitamin	3	14	2025-10-02	160	1.8	1	1	NA	NA
Vitamin-3	Vitamin	3	15	2025-10-03	161	-0.3	-1.09999999999999	1	NA	NA
Vitamin-3	Vitamin	3	16	2025-10-04	162	-0.1	-0.900000000000006	1	NA	NA
Vitamin-3	Vitamin	3	17	2025-10-05	163	-0.4	-1.19999999999999	1	NA	NA
Vitamin-3	Vitamin	3	18	2025-10-06	164	0.1	-0.699999999999989	1	NA	NA
Vitamin-3	Vitamin	3	19	2025-10-07	165	0.5	-0.299999999999983	1	NA	NA
Vitamin-3	Vitamin	3	20	2025-10-08	166	-1	-1.79999999999998	1	NA	NA
Vitamin-3	Vitamin	3	21	2025-10-09	167	-2.6	-3.40000000000001	1	NA	NA
Vitamin-3	Vitamin	3	22	2025-10-10	168	-2.7	-3.5	1	NA	NA
Vitamin-3	Vitamin	3	23	2025-10-11	169	-3.8	-4.59999999999999	1	NA	NA
Vitamin-3	Vitamin	3	24	2025-10-12	170	-3.3	-4.09999999999999	1	NA	NA
Vitamin-3	Vitamin	3	25	2025-10-13	171	-0.2	-1	1	NA	NA
Vitamin-3	Vitamin	3	26	2025-10-14	172	1	0.200000000000017	1	NA	NA
Vitamin-3	Vitamin	3	27	2025-10-15	173	0.7	-0.0999999999999943	1	NA	NA
Vitamin-3	Vitamin	3	28	2025-10-16	174	0	-0.799999999999983	1	NA	NA
Vitamin-3	Vitamin	3	29	2025-10-17	175	0.2	-0.599999999999994	1	NA	NA
Vitamin-3	Vitamin	3	30	2025-10-18	176	NA	NA	1	1	NA
NoVitamin-3	NoVitamin	3	0	2025-10-22	180	0	0.400000000000006	0	NA
NoVitamin-3	NoVitamin	3	1	2025-10-23	181	-0.5	-0.0999999999999943	0	NA
NoVitamin-3	NoVitamin	3	2	2025-10-24	182	1.8	2.20000000000002	0	NA
NoVitamin-3	NoVitamin	3	3	2025-10-25	183	0.4	0.800000000000011	0	NA
NoVitamin-3	NoVitamin	3	4	2025-10-26	184	NA	NA	0	NA	Didn't weight myself
NoVitamin-3	NoVitamin	3	5	2025-10-27	185	2.7	3.09999999999999	0	NA
NoVitamin-3	NoVitamin	3	6	2025-10-28	186	1.5	1.90000000000001	0	NA
NoVitamin-3	NoVitamin	3	7	2025-10-29	187	-0.9	-0.5	0	NA
NoVitamin-3	NoVitamin	3	8	2025-10-30	188	-0.4	0	0	NA
NoVitamin-3	NoVitamin	3	9	2025-10-31	189	1.5	1.90000000000001	0	NA
NoVitamin-3	NoVitamin	3	10	2025-11-01	190	NA	NA	0	NA	Didn't weight myself
NoVitamin-3	NoVitamin	3	11	2025-11-02	191	NA	NA	0	NA	Didn't weight myself
NoVitamin-3	NoVitamin	3	12	2025-11-03	192	3.8	4.20000000000002	0	NA
NoVitamin-3	NoVitamin	3	13	2025-11-04	193	2.2	2.59999999999999	0	NA
NoVitamin-3	NoVitamin	3	14	2025-11-05	194	3.7	4.09999999999999	0	NA
NoVitamin-3	NoVitamin	3	15	2025-11-06	195	2.3	2.70000000000002	0	NA
NoVitamin-3	NoVitamin	3	16	2025-11-07	196	4.6	5	0	NA
NoVitamin-3	NoVitamin	3	17	2025-11-08	197	NA	NA	0	NA	Didn't weight myself
NoVitamin-3	NoVitamin	3	18	2025-11-09	198	NA	NA	0	NA	Didn't weight myself
NoVitamin-3	NoVitamin	3	19	2025-11-10	199	2	2.40000000000001	0	NA
NoVitamin-3	NoVitamin	3	20	2025-11-11	200	2.8	3.20000000000002	0	NA
NoVitamin-3	NoVitamin	3	21	2025-11-12	201	4.8	5.20000000000002	0	NA
NoVitamin-3	NoVitamin	3	22	2025-11-13	202	3	3.40000000000001	0	NA
NoVitamin-3	NoVitamin	3	23	2025-11-14	203	NA	NA	0	1
NoVitamin-3	NoVitamin	3	24	2025-11-15	204	NA	NA	0	1
NoVitamin-3	NoVitamin	3	25	2025-11-16	205	NA	NA	0	NA	After travel day
NoVitamin-3	NoVitamin	3	26	2025-11-17	206	NA	NA	0	NA	After travel day
NoVitamin-3	NoVitamin	3	27	2025-11-18	207	5.4	5.80000000000001	0	NA
NoVitamin-3	NoVitamin	3	28	2025-11-19	208	4.2	4.59999999999999	0	NA
NoVitamin-3	NoVitamin	3	29	2025-11-20	209	5.8	6.20000000000002	0	NA
NoVitamin-3	NoVitamin	3	30	2025-11-21	210	5.7	6.09999999999999	0	NA