cause image
gauge image
effect image

This individual's Guiltiness is generally lowest after a daily total of 0.24 serving of 1000 Mg Vitamin C consumption over the previous 7 days.
Join This Study
Go To Interactive Study
Blue represents the sum of 1000 Mg Vitamin C consumption over the previous 7 days
An increase in 7 days cumulative 1000 Mg Vitamin C consumption is usually followed by an decrease in Guiltiness. (R = -0.141)
Typical values for Guiltiness following a given amount of 1000 Mg Vitamin C consumption over the previous 7 days.
Typical 1000 Mg Vitamin C consumption seen over the previous 7 days preceding the given Guiltiness value.
This chart shows how your 1000 Mg Vitamin C changes over time.
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for 1000 Mg Vitamin C on each day of the week.
This chart shows the typical value recorded for 1000 Mg Vitamin C for each month of the year.
This chart shows how your Guiltiness changes over time.
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for Guiltiness on each day of the week.
This chart shows the typical value recorded for Guiltiness for each month of the year.

Abstract

This individual's Guiltiness is generally 7% lower than normal after 0.23999999463558 serving 1000 Mg Vitamin C per 7 days. This individual's data suggests with a medium degree of confidence (p=0.041448748682245, 95% CI -0.383 to 0.101) that 1000 Mg Vitamin C has a weakly negative predictive relationship (R=-0.14) with Guiltiness. The highest quartile of Guiltiness measurements were observed following an average 0.18 serving 1000 Mg Vitamin C per day. The lowest quartile of Guiltiness measurements were observed following an average 0.2093749953201 serving 1000 Mg Vitamin C per day.Guiltiness is generally 7% lower than normal after a total of 0.2093749953201 serving of 1000 Mg Vitamin C consumption over the previous 7 days. Guiltiness is generally 9% higher after a total of 0.18 serving of 1000 Mg Vitamin C consumption over the previous 7 days.

Objective

The objective of this study is to determine the nature of the relationship (if any) between 1000 Mg Vitamin C and Guiltiness. Additionally, we attempt to determine the 1000 Mg Vitamin C values most likely to produce optimal Guiltiness values.

Participant Instructions

Get MyFitnessPal here and use it to record your 1000 Mg Vitamin C. Once you have a MyFitnessPal account, you can import your data from the Import Data page. This individual's data will automatically be imported and analyzed.
Record your Guiltiness daily in the reminder inbox or using the interactive web or mobile notifications.

Design

This study is based on data donated by one participant. Thus, the study design is consistent with an n=1 observational natural experiment.

Data Analysis

1000 Mg Vitamin C Pre-Processing
1000 Mg Vitamin C measurement values below 0 serving were assumed erroneous and removed. 1000 Mg Vitamin C measurement values above 30 serving were assumed erroneous and removed. It was assumed that any gaps in 1000 Mg Vitamin C data were unrecorded 0 serving measurement values.
1000 Mg Vitamin C Analysis Settings

Guiltiness Pre-Processing
Guiltiness measurement values below 1 out of 5 were assumed erroneous and removed. Guiltiness measurement values above 5 out of 5 were assumed erroneous and removed. No missing data filling value was defined for Guiltiness so any gaps in data were just not analyzed instead of assuming zero values for those times.
Guiltiness Analysis Settings

Predictive Analytics
It was assumed that 0.5 hours would pass before a change in 1000 Mg Vitamin C would produce an observable change in Guiltiness. It was assumed that 1000 Mg Vitamin C could produce an observable change in Guiltiness for as much as 7 days after the stimulus event.
Predictive Analysis Settings

Data Quantity
128 raw 1000 Mg Vitamin C measurements with 67 changes spanning 123 days from 2014-03-14 to 2014-07-15 were used in this analysis. 2800 raw Guiltiness measurements with 661 changes spanning 1964 days from 2013-11-17 to 2019-04-04 were used in this analysis.

Data Sources

1000 Mg Vitamin C data was primarily collected using MyFitnessPal. Lose weight with MyFitnessPal, the fastest and easiest-to-use calorie counter for iPhone and iPad. With the largest food database of any iOS calorie counter (over 3,000,000 foods), and amazingly fast food and exercise entry.

Guiltiness data was primarily collected using QuantiModo. QuantiModo allows you to easily track mood, symptoms, or any outcome you want to optimize in a fraction of a second. You can also import your data from over 30 other apps and devices. QuantiModo then analyzes your data to identify which hidden factors are most likely to be influencing your mood or symptoms.

Limitations

As with any human experiment, it was impossible to control for all potentially confounding variables. Correlation does not necessarily imply causation. We can never know for sure if one factor is definitely the cause of an outcome. However, lack of correlation definitely implies the lack of a causal relationship. Hence, we can with great confidence rule out non-existent relationships. For instance, if we discover no relationship between mood and an antidepressant this information is just as or even more valuable than the discovery that there is a relationship.
We can also take advantage of several characteristics of time series data from many subjects to infer the likelihood of a causal relationship if we do find a correlational relationship. The criteria for causation are a group of minimal conditions necessary to provide adequate evidence of a causal relationship between an incidence and a possible consequence.

The list of the criteria is as follows:
Strength (A.K.A. Effect Size)
A small association does not mean that there is not a causal effect, though the larger the association, the more likely that it is causal. There is a weakly negative relationship between 1000 Mg Vitamin C consumption and Guiltiness

Consistency (A.K.A. Reproducibility)
Consistent findings observed by different persons in different places with different samples strengthens the likelihood of an effect. Furthermore, in accordance with the law of large numbers (LLN), the predictive power and accuracy of these results will continually grow over time. 119 paired data points were used in this analysis. Assuming that the relationship is merely coincidental, as the participant independently modifies their 1000 Mg Vitamin C consumption values, the observed strength of the relationship will decline until it is below the threshold of significance. To it another way, in the case that we do find a spurious correlation, suggesting that banana intake improves mood for instance, one will likely increase their banana intake. Due to the fact that this correlation is spurious, it is unlikely that you will see a continued and persistent corresponding increase in mood. So over time, the spurious correlation will naturally dissipate.

Specificity
Causation is likely if a very specific population at a specific site and disease with no other likely explanation. The more specific an association between a factor and an effect is, the bigger the probability of a causal relationship.

Temporality
The effect has to occur after the cause (and if there is an expected delay between the cause and expected effect, then the effect must occur after that delay). The confidence in a causal relationship is bolstered by the fact that time-precedence was taken into account in all calculations.

Biological Gradient
Greater exposure should generally lead to greater incidence of the effect. However, in some cases, the mere presence of the factor can trigger the effect. In other cases, an inverse proportion is observed: greater exposure leads to lower incidence.

Plausibility
A plausible bio-chemical mechanism between cause and effect is critical. This is where human brains excel. Based on our responses so far, 1 humans feel that there is a plausible mechanism of action and 0 feel that any relationship observed between 1000 Mg Vitamin C consumption and Guiltiness is coincidental.

Coherence
Coherence between epidemiological and laboratory findings increases the likelihood of an effect. It will be very enlightening to aggregate this data with the data from other participants with similar genetic, diseasomic, environmentomic, and demographic profiles.

Experiment
All of human life can be considered a natural experiment. Occasionally, it is possible to appeal to experimental evidence.

Analogy
The effect of similar factors may be considered.

Relationship Statistics

Property Value
Cause Variable Name 1000 Mg Vitamin C consumption
Effect Variable Name Guiltiness
Sinn Predictive Coefficient 0.1365
Confidence Level medium
Confidence Interval 0.24199573845863
Forward Pearson Correlation Coefficient -0.141
Critical T Value 1.646
Total 1000 Mg Vitamin C consumption Over Previous 7 days Before ABOVE Average Guiltiness 0.18 serving
Total 1000 Mg Vitamin C consumption Over Previous 7 days Before BELOW Average Guiltiness 0.209 serving
Duration of Action 7 days
Effect Size weakly negative
Number of Paired Measurements 119
Optimal Pearson Product 0.025219390657337
P Value 0.041448748682245
Statistical Significance 0.8336
Strength of Relationship 0.24199573845863
Study Type individual
Analysis Performed At 2019-04-04

1000 Mg Vitamin C Statistics

Property Value
Variable Name 1000 Mg Vitamin C
Aggregation Method SUM
Analysis Performed At 2018-12-22
Duration of Action 7 days
Kurtosis 52.948814135243
Maximum Allowed Value 30 serving
Mean 0.0021567 serving
Median 0 serving
Minimum Allowed Value 0 serving
Number of Changes 67
Number of Correlations 179
Number of Measurements 128
Onset Delay 30 minutes
Standard Deviation 0.01306339191582
Unit Serving
Variable ID 54018
Variance 0.00017065220834631

Guiltiness Statistics

Property Value
Variable Name Guiltiness
Aggregation Method MEAN
Analysis Performed At 2019-04-04
Duration of Action 24 hours
Kurtosis 3.1224153723756
Maximum Allowed Value 5 out of 5
Mean 2.1627 out of 5
Median 2 out of 5
Minimum Allowed Value 1 out of 5
Number of Changes 661
Number of Correlations 5379
Number of Measurements 2800
Onset Delay 0 seconds
Standard Deviation 0.92130141512025
Unit 1 to 5 Rating
Variable ID 1335
Variance 0.84879629750257

Tracking 1000 Mg Vitamin C

Get MyFitnessPal here and use it to record your 1000 Mg Vitamin C. Once you have a MyFitnessPal account, you can import your data from the Import Data page. This individual's data will automatically be imported and analyzed.

Tracking Guiltiness

Record your Guiltiness daily in the reminder inbox or using the interactive web or mobile notifications.
Join This Study

https://lh6.googleusercontent.com/-BHr4hyUWqZU/AAAAAAAAAAI/AAAAAAAIG28/2Lv0en738II/photo.jpg Principal Investigator - Mike Sinn