Your Overall Mood is generally highest after an average of 1.8 out of 5 of Inflammatory Pain over the previous 7 days.
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Blue represents the mean of Inflammatory Pain over the previous 7 days
An increase in 7 days cumulative Inflammatory Pain is usually followed by an decrease in Overall Mood. (R = -0.596)
Typical values for Overall Mood following a given amount of Inflammatory Pain over the previous 7 days.
Typical Inflammatory Pain seen over the previous 7 days preceding the given Overall Mood value.
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.
This chart shows how your Overall Mood changes over time.
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for Overall Mood on each day of the week.
This chart shows the typical value recorded for Overall Mood for each month of the year.

Abstract

You recorded 1.4 out of 5 Inflammatory Pain 6 years ago. Your Overall Mood is generally generally 8% higher than normal after an average of1.8 out of 5 Inflammatory Pain over the previous 7 days. Your data suggests with a high degree of confidence (p=5.801687923287E-5, 95% CI -0.79 to -0.402) that Inflammatory Pain has a moderately negative predictive relationship (R=-0.6) with Overall Mood. The highest quartile of Overall Mood measurements were observed following an average 1.89 out of 5 Inflammatory Pain. The lowest quartile of Overall Mood measurements were observed following an average 2.4379310344828 /5 Inflammatory Pain.Overall Mood is generally generally 5% lower than normal after an average of 2.4379310344828 out of 5 of Inflammatory Pain over the previous 7 days. Overall Mood is generally 8% higher after an average of 1.89 out of 5 of Inflammatory Pain over the previous 7 days.

Objective

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

Participant Instructions

Record your Inflammatory Pain daily in the reminder inbox or using the interactive web or mobile notifications.
Record your Overall Mood 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

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

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

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

Data Quantity
93 raw Inflammatory Pain measurements with 37 changes spanning 87 days from 2013-01-12 to 2013-04-09 were used in this analysis. 13251 raw Overall Mood measurements with 1161 changes spanning 2458 days from 2012-05-06 to 2019-01-28 were used in this analysis.

Data Sources

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.

Overall Mood 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 correlation. 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 negative relationship between Inflammatory Pain and Overall Mood

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 Inflammatory Pain 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, 40 humans feel that there is a plausible mechanism of action and 3 feel that any relationship observed between Inflammatory Pain and Overall Mood 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 Inflammatory Pain
Effect Variable Name Overall Mood
Sinn Predictive Coefficient 0.353
Confidence Level high
Confidence Interval 0.1944812624638
Forward Pearson Correlation Coefficient -0.596
Critical T Value 1.671
Average Inflammatory Pain Over Previous 7 days Before ABOVE Average Overall Mood 1.89 out of 5
Average Inflammatory Pain Over Previous 7 days Before BELOW Average Overall Mood 2.438 out of 5
Duration of Action 7 days
Effect Size moderately negative
Number of Paired Measurements 50
Optimal Pearson Product 0.61833331613842
P Value 5.801687923287E-5
Statistical Significance 0.5231
Strength of Relationship 0.1944812624638
Study Type individual
Analysis Performed At 2019-01-28

Inflammatory Pain Statistics

Property Value
Variable Name Inflammatory Pain
Aggregation Method MEAN
Analysis Performed At 2018-12-22
Duration of Action 7 days
Kurtosis 2.7508536592149
Maximum Allowed Value 5 out of 5
Mean 2.202 out of 5
Median 2.2 out of 5
Minimum Allowed Value 1 out of 5
Number of Changes 37
Number of Correlations 230
Number of Measurements 93
Onset Delay 0 seconds
Standard Deviation 0.5272642923496
Unit 1 to 5 Rating
UPC 753970618156
Variable ID 1340
Variance 0.27800763398693

Overall Mood Statistics

Property Value
Variable Name Overall Mood
Aggregation Method MEAN
Analysis Performed At 2019-01-28
Duration of Action 24 hours
Kurtosis 6.725960482864
Maximum Allowed Value 5 out of 5
Mean 2.9139 out of 5
Median 3 out of 5
Minimum Allowed Value 1 out of 5
Number of Changes 1161
Number of Correlations 4058
Number of Measurements 13251
Onset Delay 0 seconds
Standard Deviation 0.53288454678104
Unit 1 to 5 Rating
UPC 767674073845
Variable ID 1398
Variance 0.28396594019803

https://lh6.googleusercontent.com/-BHr4hyUWqZU/AAAAAAAAAAI/AAAAAAAIG28/2Lv0en738II/photo.jpg Principal Investigator - Mike Sinn