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Based on data from 2 participants, Sleep Efficiency is generally highest after a daily total of 1 serving of Gluten Free Pasta With Olive Oil consumption over the previous 7 days.
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People with higher Gluten Free Pasta With Olive Oil consumption usually have higher Sleep Efficiency
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for Gluten Free Pasta With Olive Oil on each day of the week.
This chart shows the typical value recorded for Gluten Free Pasta With Olive Oil for each month of the year.
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for Sleep Efficiency on each day of the week.
This chart shows the typical value recorded for Sleep Efficiency for each month of the year.

Abstract

Aggregated data from 2 study participants suggests with a low degree of confidence (p=0.17368360935204, 95% CI -28.611 to 28.276) that Gluten Free Pasta With Olive Oil (serving) has a weakly negative predictive relationship (R=-0.17) with Sleep Efficiency. The highest quartile of Sleep Efficiency measurements were observed following an average 0.13 serving Gluten Free Pasta With Olive Oil (serving) per day. The lowest quartile of Sleep Efficiency measurements were observed following an average 0.33333333333333 serving Gluten Free Pasta With Olive Oil (serving) per day.

Objective

The objective of this study is to determine the nature of the relationship (if any) between Gluten Free Pasta With Olive Oil and Sleep Efficiency. Additionally, we attempt to determine the Gluten Free Pasta With Olive Oil (serving) values most likely to produce optimal Sleep Efficiency values.

Participant Instructions

Record your Gluten Free Pasta With Olive Oil daily in the reminder inbox or using the interactive web or mobile notifications.
Get Fitbit here and use it to record your Sleep Efficiency. 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

Gluten Free Pasta With Olive Oil Pre-Processing
Gluten Free Pasta With Olive Oil measurement values below 0 serving were assumed erroneous and removed. Gluten Free Pasta With Olive Oil measurement values above 30 serving were assumed erroneous and removed. It was assumed that any gaps in Gluten Free Pasta With Olive Oil data were unrecorded 0 serving measurement values.
Gluten Free Pasta With Olive Oil Analysis Settings

Sleep Efficiency Pre-Processing
No minimum allowed measurement value was defined for Sleep Efficiency. No maximum allowed measurement value was defined for Sleep Efficiency. No missing data filling value was defined for Sleep Efficiency so any gaps in data were just not analyzed instead of assuming zero values for those times.
Sleep Efficiency Analysis Settings

Predictive Analytics
It was assumed that 0.5 hours would pass before a change in Gluten Free Pasta With Olive Oil (serving) would produce an observable change in Sleep Efficiency. It was assumed that Gluten Free Pasta With Olive Oil (serving) could produce an observable change in Sleep Efficiency for as much as 7 days after the stimulus event.
Predictive Analysis Settings

Data Sources

Gluten Free Pasta With Olive Oil (serving) 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.

Sleep Efficiency 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 Gluten Free Pasta With Olive Oil consumption and Sleep Efficiency

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. 43 paired data points were used in this analysis. Assuming that the relationship is merely coincidental, as the participant independently modifies their Gluten Free Pasta With Olive Oil 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 Gluten Free Pasta With Olive Oil consumption and Sleep Efficiency 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 Gluten Free Pasta With Olive Oil consumption
Effect Variable Name Sleep Efficiency
Sinn Predictive Coefficient 0.010586100994895
Confidence Level low
Confidence Interval 28.443534809889
Forward Pearson Correlation Coefficient -0.1672
Critical T Value 1.6965
Total Gluten Free Pasta With Olive Oil consumption Over Previous 7 days Before ABOVE Average Sleep Efficiency 0.13 serving
Total Gluten Free Pasta With Olive Oil consumption Over Previous 7 days Before BELOW Average Sleep Efficiency 0.33333333333333 serving
Duration of Action 7 days
Effect Size weakly negative
Number of Paired Measurements 43
Optimal Pearson Product 0.43863753843877
P Value 0.17368360935204
Statistical Significance 0.066399998497218
Strength of Relationship 28.443534809889
Study Type population
Analysis Performed At 2019-04-04
Number of Participants 2

Gluten Free Pasta With Olive Oil Statistics

Property Value
Variable Name Gluten Free Pasta With Olive Oil (serving)
Aggregation Method SUM
Analysis Performed At 2018-12-22
Duration of Action 7 days
Kurtosis 23.930882574621
Maximum Allowed Value 30 serving
Mean 0.047226 serving
Median 0 serving
Minimum Allowed Value 0 serving
Number of Correlations 47
Number of Measurements 30
Onset Delay 30 minutes
Standard Deviation 0.21886485223214
Unit Serving
Variable ID 109322
Variance 0.048174976750004

Sleep Efficiency Statistics

Property Value
Variable Name Sleep Efficiency
Aggregation Method MEAN
Analysis Performed At 2018-12-22
Duration of Action 24 hours
Kurtosis 10.116231860745
Mean 87.550074074074 percent
Median 88.418518518519 percent
Number of Correlations 339
Number of Measurements 22405
Onset Delay 0 seconds
Standard Deviation 6.0946131489375
Unit Percent
UPC 878881000699
Variable ID 5211811
Variance 78.854434460161


Tracking Gluten Free Pasta With Olive Oil

Record your Gluten Free Pasta With Olive Oil daily in the reminder inbox or using the interactive web or mobile notifications.

Tracking Sleep Efficiency

Get Fitbit here and use it to record your Sleep Efficiency. 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