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This individual's Energy is generally highest after an average of 1.8 out of 5 of Acne Severity over the previous 7 days.
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Blue represents the mean of Acne Severity over the previous 7 days
An increase in 7 days cumulative Acne Severity is usually followed by an decrease in Energy. (R = -0.15)
Typical values for Energy following a given amount of Acne Severity over the previous 7 days.
Typical Acne Severity seen over the previous 7 days preceding the given Energy value.
This chart shows how your Acne Severity changes over time.
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for Acne Severity on each day of the week.
This chart shows the typical value recorded for Acne Severity for each month of the year.
This chart shows how your Energy changes over time.
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for Energy on each day of the week.
This chart shows the typical value recorded for Energy for each month of the year.

Abstract

This individual's Energy is generally 5% higher than normal after an average of 1.84 out of 5 Acne Severity over the previous 7 days. This individual's data suggests with a high degree of confidence (p=1.1551004003897E-9, 95% CI -0.21 to -0.09) that Acne Severity has a weakly negative predictive relationship (R=-0.15) with Energy. The highest quartile of Energy measurements were observed following an average 1.86 out of 5 Acne Severity. The lowest quartile of Energy measurements were observed following an average 2.0570875420875 /5 Acne Severity.Energy is generally 3% lower than normal after an average of 2.0570875420875 out of 5 of Acne Severity over the previous 7 days. Energy is generally 5% higher after an average of 1.86 out of 5 of Acne Severity over the previous 7 days.

Objective

The objective of this study is to determine the nature of the relationship (if any) between Acne Severity and Energy. Additionally, we attempt to determine the Acne Severity values most likely to produce optimal Energy values.

Participant Instructions

Record your Acne Severity daily in the reminder inbox or using the interactive web or mobile notifications.
Record your Energy 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

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

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

Predictive Analytics
It was assumed that 0 hours would pass before a change in Acne Severity would produce an observable change in Energy. It was assumed that Acne Severity could produce an observable change in Energy for as much as 7 days after the stimulus event.
Predictive Analysis Settings

Data Quantity
1297 raw Acne Severity measurements with 396 changes spanning 2271 days from 2013-01-12 to 2019-04-03 were used in this analysis. 1085 raw Energy measurements with 318 changes spanning 2271 days from 2013-01-12 to 2019-04-03 were used in this analysis.

Data Sources

Acne Severity 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.

Energy 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 Acne Severity and Energy

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. 746 paired data points were used in this analysis. Assuming that the relationship is merely coincidental, as the participant independently modifies their Acne Severity 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 Acne Severity and Energy 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 Acne Severity
Effect Variable Name Energy
Sinn Predictive Coefficient 0.1772
Confidence Level high
Confidence Interval 0.059834895264137
Forward Pearson Correlation Coefficient -0.15
Critical T Value 1.646
Average Acne Severity Over Previous 7 days Before ABOVE Average Energy 1.86 out of 5
Average Acne Severity Over Previous 7 days Before BELOW Average Energy 2.057 out of 5
Duration of Action 7 days
Effect Size weakly negative
Number of Paired Measurements 746
Optimal Pearson Product 0.04179734362353
P Value 1.1551004003897E-9
Statistical Significance 1
Strength of Relationship 0.059834895264137
Study Type individual
Analysis Performed At 2019-04-04

Acne Severity Statistics

Property Value
Variable Name Acne Severity
Aggregation Method MEAN
Analysis Performed At 2019-04-05
Duration of Action 7 days
Kurtosis 2.8229889482101
Maximum Allowed Value 5 out of 5
Mean 1.9571 out of 5
Median 2 out of 5
Minimum Allowed Value 1 out of 5
Number of Changes 396
Number of Correlations 2266
Number of Measurements 1297
Onset Delay 0 seconds
Standard Deviation 0.74609946573708
Unit 1 to 5 Rating
UPC 837654497159
Variable ID 1251
Variance 0.55666441277315

Energy Statistics

Property Value
Variable Name Energy
Aggregation Method MEAN
Analysis Performed At 2019-04-03
Duration of Action 24 hours
Kurtosis 3.8227578782624
Maximum Allowed Value 5 out of 5
Mean 2.9978 out of 5
Median 3 out of 5
Minimum Allowed Value 1 out of 5
Number of Changes 318
Number of Correlations 1967
Number of Measurements 1085
Onset Delay 0 seconds
Standard Deviation 0.67886489832525
Unit 1 to 5 Rating
UPC 637769766115
Variable ID 1306
Variance 0.46085755017816

Tracking Acne Severity

Record your Acne Severity daily in the reminder inbox or using the interactive web or mobile notifications.

Tracking Energy

Record your Energy daily in the reminder inbox or using the interactive web or mobile notifications.
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https://lh6.googleusercontent.com/-BHr4hyUWqZU/AAAAAAAAAAI/AAAAAAAIG28/2Lv0en738II/photo.jpg Principal Investigator - Mike Sinn