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Based on data from 2 participants, Body Weight is generally highest after a daily total of 400 milligrams of CoQ10 By Doctors Best intake over the previous 7 days.
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People with higher CoQ10 By Doctors Best intake usually have lower Body Weight
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for CoQ10 By Doctors Best on each day of the week.
This chart shows the typical value recorded for CoQ10 By Doctors Best for each month of the year.
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for Body Weight on each day of the week.
This chart shows the typical value recorded for Body Weight for each month of the year.

Abstract

Aggregated data from 2 study participants suggests with a medium degree of confidence (p=0.019224943045016, 95% CI -1.437 to 0.803) that CoQ10 By Doctors Best has a moderately negative predictive relationship (R=-0.32) with Body Weight. The highest quartile of Body Weight measurements were observed following an average 214 milligrams CoQ10 By Doctors Best per day. The lowest quartile of Body Weight measurements were observed following an average 319.64285714286 mg CoQ10 By Doctors Best per day.

Objective

The objective of this study is to determine the nature of the relationship (if any) between CoQ10 By Doctors Best and Body Weight. Additionally, we attempt to determine the CoQ10 By Doctors Best values most likely to produce optimal Body Weight values.

Participant Instructions

Record your CoQ10 By Doctors Best daily in the reminder inbox or using the interactive web or mobile notifications.
Get Fitbit here and use it to record your Body Weight. Once you have a Fitbit account, you can import your data from the Import Data page. This individual's data will automatically be imported and analyzed.

Design

This study is based on data donated by 2 participants. Thus, the study design is equivalent to the aggregation of 2 separate n=1 observational natural experiments.

Data Analysis

CoQ10 By Doctors Best Pre-Processing
CoQ10 By Doctors Best measurement values below 0 milligrams were assumed erroneous and removed. No maximum allowed measurement value was defined for CoQ10 By Doctors Best. It was assumed that any gaps in CoQ10 By Doctors Best data were unrecorded 0 milligrams measurement values.
CoQ10 By Doctors Best Analysis Settings

Body Weight Pre-Processing
Body Weight measurement values below 0 pounds were assumed erroneous and removed. Body Weight measurement values above 1000 pounds were assumed erroneous and removed. No missing data filling value was defined for Body Weight so any gaps in data were just not analyzed instead of assuming zero values for those times.
Body Weight Analysis Settings

Predictive Analytics
It was assumed that 0.5 hours would pass before a change in CoQ10 By Doctors Best would produce an observable change in Body Weight. It was assumed that CoQ10 By Doctors Best could produce an observable change in Body Weight for as much as 7 days after the stimulus event.
Predictive Analysis Settings

Data Sources

CoQ10 By Doctors Best 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.

Body Weight data was primarily collected using Fitbit. Fitbit makes activity tracking easy and automatic.

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 moderately negative relationship between CoQ10 By Doctors Best intake and Body Weight

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. 382 paired data points were used in this analysis. Assuming that the relationship is merely coincidental, as the participant independently modifies their CoQ10 By Doctors Best intake 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 CoQ10 By Doctors Best intake and Body Weight 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 CoQ10 By Doctors Best intake
Effect Variable Name Body Weight
Sinn Predictive Coefficient 0.031783865978175
Confidence Level medium
Confidence Interval 1.1198683428128
Forward Pearson Correlation Coefficient -0.3171
Critical T Value 1.6585
Total Co Q10 By Doctors Best intake Over Previous 7 days Before ABOVE Average Body Weight 214 milligrams
Total Co Q10 By Doctors Best intake Over Previous 7 days Before BELOW Average Body Weight 319.64285714286 milligrams
Duration of Action 7 days
Effect Size moderately negative
Number of Paired Measurements 382
Optimal Pearson Product 0.56221581223213
P Value 0.019224943045016
Statistical Significance 0.65584999322891
Strength of Relationship 1.1198683428128
Study Type population
Analysis Performed At 2019-04-06
Number of Participants 2

CoQ10 By Doctors Best Statistics

Property Value
Variable Name CoQ10 By Doctors Best
Aggregation Method SUM
Analysis Performed At 2018-12-22
Duration of Action 7 days
Kurtosis 39.922302815044
Mean 11.511326666667 milligrams
Median 0 milligrams
Minimum Allowed Value 0 milligrams
Number of Correlations 65
Number of Measurements 954
Onset Delay 30 minutes
Standard Deviation 28.236515863566
Unit Milligrams
UPC 753950003323
Variable ID 5627141
Variance 993.66573881044

Body Weight Statistics

Property Value
Variable Name Body Weight
Aggregation Method MEAN
Analysis Performed At 2019-02-02
Duration of Action 7 days
Kurtosis 25.470204651548
Maximum Allowed Value 1000 pounds
Mean 168.97283090379 pounds
Median 169.42999976732 pounds
Minimum Allowed Value 0 pounds
Number of Correlations 966
Number of Measurements 76334
Onset Delay 0 seconds
Standard Deviation 184.51819331854
Unit Pounds
UPC 875011003902
Variable ID 1486
Variance 8495258.0892244

Tracking CoQ10 By Doctors Best

Record your CoQ10 By Doctors Best daily in the reminder inbox or using the interactive web or mobile notifications.

Tracking Body Weight

Get Fitbit here and use it to record your Body Weight. Once you have a Fitbit account, you can import your data from the Import Data page. This individual's data will automatically be imported and analyzed.
Join This Study

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