This individual's Inflammatory Pain is generally lowest after an average of 0.29 applications of Hand Lotion over the previous 7 days.
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Blue represents the mean of Hand Lotion over the previous 7 days
An increase in 7 days cumulative Hand Lotion is usually followed by an increase in Inflammatory Pain. (R = 0.412)
Typical values for Inflammatory Pain following a given amount of Hand Lotion over the previous 7 days.
Typical Hand Lotion seen over the previous 7 days preceding the given Inflammatory Pain value.
This chart shows how your Hand Lotion changes over time.
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for Hand Lotion on each day of the week.
This chart shows the typical value recorded for Hand Lotion for each month of the year.
This chart shows how your Inflammatory Pain changes over time.
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for Inflammatory Pain on each day of the week.
This chart shows the typical value recorded for Inflammatory Pain for each month of the year.

Abstract

This individual's Inflammatory Pain is generally 6.52% lower than normal after 0.28571428571429 applications Hand Lotion (applications) per 7 days. This individual's data suggests with a medium degree of confidence (p=0.048633543478933, 95% CI 0.174 to 0.65) that Hand Lotion (applications) has a moderately positive predictive relationship (R=0.41) with Inflammatory Pain. The highest quartile of Inflammatory Pain measurements were observed following an average 0.7 applications Hand Lotion (applications). The lowest quartile of Inflammatory Pain measurements were observed following an average 0.45601851851852 applications Hand Lotion (applications).Inflammatory Pain is generally 6.52% lower than normal after an average of 0.45601851851852 applications of Hand Lotion over the previous 7 days. Inflammatory Pain is generally 6.78% higher after an average of 0.7 applications of Hand Lotion over the previous 7 days.

Objective

The objective of this study is to determine the nature of the relationship (if any) between Hand Lotion and Inflammatory Pain. Additionally, we attempt to determine the Hand Lotion (applications) values most likely to produce optimal Inflammatory Pain values.

Participant Instructions

Get GitHub here and use it to record your Hand Lotion. Once you have a GitHub account, you can import your data from the Import Data page. This individual's data will automatically be imported and analyzed.
Record your Inflammatory Pain 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

Hand Lotion Pre-Processing
Hand Lotion measurement values below 0 applications were assumed erroneous and removed. Hand Lotion measurement values above 20 applications were assumed erroneous and removed. It was assumed that any gaps in Hand Lotion data were unrecorded 0 applications measurement values.
Hand Lotion Analysis Settings

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

Predictive Analytics
It was assumed that 0.5 hours would pass before a change in Hand Lotion (applications) would produce an observable change in Inflammatory Pain. It was assumed that Hand Lotion (applications) could produce an observable change in Inflammatory Pain for as much as 7 days after the stimulus event.
Predictive Analysis Settings

Data Quantity
113 raw Hand Lotion (applications) measurements with 55 changes spanning 242 days from 2012-07-25 to 2013-03-24 were used in this analysis. 159 raw Inflammatory Pain measurements with 68 changes spanning 2353 days from 2013-01-12 to 2019-06-23 were used in this analysis.

Data Sources

Hand Lotion (applications) data was primarily collected using GitHub. GitHub is the best place to share code with friends, co-workers, classmates, and complete strangers. Over four million people use GitHub to build amazing things together.

Inflammatory Pain 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 moderately positive relationship between Hand Lotion and Inflammatory Pain

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. 51 paired data points were used in this analysis. Assuming that the relationship is merely coincidental, as the participant independently modifies their Hand Lotion 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 Hand Lotion and Inflammatory Pain 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 Hand Lotion
Effect Variable Name Inflammatory Pain
Sinn Predictive Coefficient 0.1878
Confidence Level medium
Confidence Interval 0.23843304051273
Forward Pearson Correlation Coefficient 0.412
Critical T Value 1.671
Average Hand Lotion Over Previous 7 days Before ABOVE Average Inflammatory Pain 0.7 applications
Average Hand Lotion Over Previous 7 days Before BELOW Average Inflammatory Pain 0.456 applications
Duration of Action 7 days
Effect Size moderately positive
Number of Paired Measurements 51
Optimal Pearson Product 0.30562354583738
P Value 0.048633543478933
Statistical Significance 0.45588693117797
Strength of Relationship 0.23843304051273
Study Type individual
Analysis Performed At 2019-06-24

Hand Lotion Statistics

Property Value
Variable Name Hand Lotion (applications)
Aggregation Method MEAN
Analysis Performed At 2018-12-22
Duration of Action 7 days
Kurtosis 27.538581662011
Maximum Allowed Value 20 applications
Mean 0.033909 applications
Median 0 applications
Minimum Allowed Value 0 applications
Number of Changes 55
Number of Correlations 56
Number of Measurements 113
Onset Delay 30 minutes
Standard Deviation 0.18074193250038
Unit Applications
UPC 813396023269
Variable ID 1338
Variance 0.032667646163972

Inflammatory Pain Statistics

Property Value
Variable Name Inflammatory Pain
Aggregation Method MEAN
Analysis Performed At 2019-06-24
Duration of Action 7 days
Kurtosis 3.6463138790869
Maximum Allowed Value 5 out of 5
Mean 2.4064 out of 5
Median 2.2 out of 5
Minimum Allowed Value 1 out of 5
Number of Changes 68
Number of Correlations 376
Number of Measurements 159
Onset Delay 0 seconds
Standard Deviation 0.88179153896702
Unit 1 to 5 Rating
UPC 753970618156
Variable ID 1340
Variance 0.77755631819383

Tracking Hand Lotion

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

Tracking Inflammatory Pain

Record your Inflammatory Pain 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