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This individual's Energy is generally highest after a daily total of 20 milligrams of Deprenyl (Selegiline) intake over the previous 7 days.
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Blue represents the sum of Deprenyl (Selegiline) intake over the previous 7 days
An increase in 7 days cumulative Deprenyl (Selegiline) intake is usually followed by an increase in Energy. (R = 0.281)
Typical values for Energy following a given amount of Deprenyl (Selegiline) intake over the previous 7 days.
Typical Deprenyl (Selegiline) intake seen over the previous 7 days preceding the given Energy value.
This chart shows how your Deprenyl (Selegiline) changes over time.
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for Deprenyl (Selegiline) on each day of the week.
This chart shows the typical value recorded for Deprenyl (Selegiline) 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 11% higher than normal after a total of 20 milligrams Deprenyl (Selegiline) intake over the previous 7 days. This individual's data suggests with a high degree of confidence (p=6.4195933328858E-6, 95% CI 0.126 to 0.436) that Deprenyl (Selegiline) has a weakly positive predictive relationship (R=0.28) with Energy. The highest quartile of Energy measurements were observed following an average 17.83 milligrams Deprenyl (Selegiline) per day. The lowest quartile of Energy measurements were observed following an average 3.7621359223301 mg Deprenyl (Selegiline) per day.Energy is generally 4% lower than normal after a total of 3.7621359223301 milligrams of Deprenyl (Selegiline) intake over the previous 7 days. Energy is generally 11% higher after a total of 17.83 milligrams of Deprenyl (Selegiline) intake over the previous 7 days.

Objective

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

Participant Instructions

Get Fitbit here and use it to record your Deprenyl (Selegiline). 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.
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

Deprenyl (Selegiline) Pre-Processing
Deprenyl (Selegiline) measurement values below 0 milligrams were assumed erroneous and removed. No maximum allowed measurement value was defined for Deprenyl (Selegiline). It was assumed that any gaps in Deprenyl (Selegiline) data were unrecorded 0 milligrams measurement values.
Deprenyl (Selegiline) 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 0.5 hours would pass before a change in Deprenyl (Selegiline) would produce an observable change in Energy. It was assumed that Deprenyl (Selegiline) could produce an observable change in Energy for as much as 7 days after the stimulus event.
Predictive Analysis Settings

Data Quantity
286 raw Deprenyl (Selegiline) measurements with 88 changes spanning 1759 days from 2012-07-28 to 2017-05-22 were used in this analysis. 1079 raw Energy measurements with 317 changes spanning 2264 days from 2013-01-12 to 2019-03-27 were used in this analysis.

Data Sources

Deprenyl (Selegiline) data was primarily collected using Fitbit. Fitbit makes activity tracking easy and automatic.

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 positive relationship between Deprenyl (Selegiline) intake 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. 275 paired data points were used in this analysis. Assuming that the relationship is merely coincidental, as the participant independently modifies their Deprenyl (Selegiline) 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 Deprenyl (Selegiline) intake 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 Deprenyl (Selegiline) intake
Effect Variable Name Energy
Sinn Predictive Coefficient 0.2482
Confidence Level high
Confidence Interval 0.15472230244436
Forward Pearson Correlation Coefficient 0.281
Critical T Value 1.646
Total Deprenyl ( Selegiline) intake Over Previous 7 days Before ABOVE Average Energy 17.83 milligrams
Total Deprenyl ( Selegiline) intake Over Previous 7 days Before BELOW Average Energy 3.762 milligrams
Duration of Action 7 days
Effect Size weakly positive
Number of Paired Measurements 275
Optimal Pearson Product 0.31095625651732
P Value 6.4195933328858E-6
Statistical Significance 0.7767
Strength of Relationship 0.15472230244436
Study Type individual
Analysis Performed At 2019-04-04

Deprenyl (Selegiline) Statistics

Property Value
Variable Name Deprenyl (Selegiline)
Aggregation Method SUM
Analysis Performed At 2018-12-22
Duration of Action 7 days
Kurtosis 29.943182508068
Mean 0.3746 milligrams
Median 0 milligrams
Minimum Allowed Value 0 milligrams
Number of Changes 88
Number of Correlations 156
Number of Measurements 286
Onset Delay 30 minutes
Standard Deviation 1.419434627642
Unit Milligrams
UPC 767674242524
Variable ID 1298
Variance 2.0147946621492

Energy Statistics

Property Value
Variable Name Energy
Aggregation Method MEAN
Analysis Performed At 2019-03-29
Duration of Action 24 hours
Kurtosis 3.8009426932525
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 317
Number of Correlations 1947
Number of Measurements 1079
Onset Delay 0 seconds
Standard Deviation 0.68081005401161
Unit 1 to 5 Rating
UPC 637769766115
Variable ID 1306
Variance 0.46350232964329

Tracking Deprenyl (Selegiline)

Get Fitbit here and use it to record your Deprenyl (Selegiline). 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.

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