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This individual's Light Sleep Duration is generally highest after a daily total of 10 minutes of Meditation over the previous 7 days.
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Blue represents the sum of Meditation over the previous 7 days
An increase in 7 days cumulative Meditation is usually followed by an decrease in Light Sleep Duration. (R = -0.15)
Typical values for Light Sleep Duration following a given amount of Meditation over the previous 7 days.
Typical Meditation seen over the previous 7 days preceding the given Light Sleep Duration value.
This chart shows how your Meditation changes over time.
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for Meditation on each day of the week.
This chart shows the typical value recorded for Meditation for each month of the year.
This chart shows how your Light Sleep Duration changes over time.
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for Light Sleep Duration on each day of the week.
This chart shows the typical value recorded for Light Sleep Duration for each month of the year.

Abstract

This individual's Light Sleep Duration is generally 6.76% higher than normal after a total of 10 minutes Meditation over the previous 7 days. This individual's data suggests with a high degree of confidence (p=0.00042386901583093, 95% CI -20.479 to 20.179) that Meditation has a weakly negative predictive relationship (R=-0.15) with Light Sleep Duration. The highest quartile of Light Sleep Duration measurements were observed following an average 13 minutes Meditation per day. The lowest quartile of Light Sleep Duration measurements were observed following an average 13.795918367347 min Meditation per day.Light Sleep Duration is generally 14.19% lower than normal after a total of 14 minutes of Meditation over the previous 7 days. Light Sleep Duration is generally 6.76% higher after a total of 13 minutes of Meditation over the previous 7 days.

Objective

The objective of this study is to determine the nature of the relationship (if any) between Meditation and Light Sleep Duration. Additionally, we attempt to determine the Meditation values most likely to produce optimal Light Sleep Duration values.

Participant Instructions

Record your Meditation daily in the reminder inbox or using the interactive web or mobile notifications.
Get Fitbit here and use it to record your Light Sleep Duration. 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 one participant. Thus, the study design is consistent with an n=1 observational natural experiment.

Data Analysis

Meditation Pre-Processing
Meditation measurement values below 0 microseconds were assumed erroneous and removed. Meditation measurement values above 7 days were assumed erroneous and removed. It was assumed that any gaps in Meditation data were unrecorded 0 microseconds measurement values.
Meditation Analysis Settings

Light Sleep Duration Pre-Processing
Light Sleep Duration measurement values below 0 microseconds were assumed erroneous and removed. Light Sleep Duration measurement values above 7 days were assumed erroneous and removed. It was assumed that any gaps in Light Sleep Duration data were unrecorded 0 microseconds measurement values.
Light Sleep Duration Analysis Settings

Predictive Analytics
It was assumed that 0.5 hours would pass before a change in Meditation would produce an observable change in Light Sleep Duration. It was assumed that Meditation could produce an observable change in Light Sleep Duration for as much as 7 days after the stimulus event.
Predictive Analysis Settings

Data Quantity
873 raw Meditation measurements with 253 changes spanning 1840 days from 2014-04-29 to 2019-05-12 were used in this analysis. 323 raw Light Sleep Duration measurements with 307 changes spanning 344 days from 2018-05-06 to 2019-04-15 were used in this analysis.

Data Sources

Meditation 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.

Light Sleep Duration 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 weakly negative relationship between Meditation and Light Sleep Duration

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. 375 paired data points were used in this analysis. Assuming that the relationship is merely coincidental, as the participant independently modifies their Meditation 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 Meditation and Light Sleep Duration 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 Meditation
Effect Variable Name Light Sleep Duration
Sinn Predictive Coefficient 0.1417
Confidence Level high
Confidence Interval 20.329439876554
Forward Pearson Correlation Coefficient -0.15
Critical T Value 1.646
Total Meditation Over Previous 7 days Before ABOVE Average Light Sleep Duration 13 minutes
Total Meditation Over Previous 7 days Before BELOW Average Light Sleep Duration 14 minutes
Duration of Action 7 days
Effect Size weakly negative
Number of Paired Measurements 375
Optimal Pearson Product 0.0088957591063633
P Value 0.00042386901583093
Statistical Significance 0.94494968708644
Strength of Relationship 20.329439876554
Study Type individual
Analysis Performed At 2019-05-14

Meditation Statistics

Property Value
Variable Name Meditation
Aggregation Method SUM
Analysis Performed At 2019-05-13
Duration of Action 7 days
Kurtosis 14.261492292546
Maximum Allowed Value 7 days
Mean 79 seconds
Median 0 microseconds
Minimum Allowed Value 0 microseconds
Number of Changes 253
Number of Correlations 280
Number of Measurements 873
Onset Delay 30 minutes
Standard Deviation 3.5489294855776
Unit Minutes
UPC 640791683572
Variable ID 85055
Variance 12.594900493602

Light Sleep Duration Statistics

Property Value
Variable Name Light Sleep Duration
Aggregation Method SUM
Analysis Performed At 2019-04-16
Duration of Action 24 hours
Kurtosis 4.650999411445
Maximum Allowed Value 7 days
Mean 4 hours
Median 4 hours
Minimum Allowed Value 0 microseconds
Number of Changes 307
Number of Measurements 323
Onset Delay 0 seconds
Standard Deviation 84.925930008461
Unit Minutes
Variable ID 6054283
Variance 7212.4135878021

Tracking Meditation

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

Tracking Light Sleep Duration

Get Fitbit here and use it to record your Light Sleep Duration. 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.
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https://lh6.googleusercontent.com/-BHr4hyUWqZU/AAAAAAAAAAI/AAAAAAAIG28/2Lv0en738II/photo.jpg Principal Investigator - Mike Sinn