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This individual's Arthritic Pains is generally lowest after a daily total of 4 minutes of Peak Heart Rate Zone over the previous 24 hours.
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Blue represents the sum of Peak Heart Rate Zone over the previous 24 hours
An increase in 24 hours cumulative Peak Heart Rate Zone is usually followed by an decrease in Arthritic Pains. (R = -0.008)
Typical values for Arthritic Pains following a given amount of Peak Heart Rate Zone over the previous 24 hours.
Typical Peak Heart Rate Zone seen over the previous 24 hours preceding the given Arthritic Pains value.
This chart shows how your Peak Heart Rate Zone changes over time.
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for Peak Heart Rate Zone on each day of the week.
This chart shows the typical value recorded for Peak Heart Rate Zone for each month of the year.
This chart shows how your Arthritic Pains changes over time.
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for Arthritic Pains on each day of the week.
This chart shows the typical value recorded for Arthritic Pains for each month of the year.

Abstract

This individual's Arthritic Pains is generally 0.73% lower than normal after 4 minutes Peak Heart Rate Zone Minutes per 24 hours. This individual's data suggests with a medium degree of confidence (p=0.38394512007979, 95% CI -0.385 to 0.369) that Peak Heart Rate Zone Minutes has a very weakly negative predictive relationship (R=-0.01) with Arthritic Pains. The highest quartile of Arthritic Pains measurements were observed following an average 4 minutes Peak Heart Rate Zone Minutes per day. The lowest quartile of Arthritic Pains measurements were observed following an average 3.5421686746988 min Peak Heart Rate Zone Minutes per day.Arthritic Pains is generally 0.73% lower than normal after a total of 4 minutes of Peak Heart Rate Zone over the previous 24 hours. Arthritic Pains is generally 3.1% higher after a total of 4 minutes of Peak Heart Rate Zone over the previous 24 hours.

Objective

The objective of this study is to determine the nature of the relationship (if any) between Peak Heart Rate Zone Minutes and Arthritic Pains. Additionally, we attempt to determine the Peak Heart Rate Zone Minutes values most likely to produce optimal Arthritic Pains values.

Participant Instructions

Get Fitbit here and use it to record your Peak Heart Rate Zone. 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 Arthritic Pains 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

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

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

Predictive Analytics
It was assumed that 0 hours would pass before a change in Peak Heart Rate Zone Minutes would produce an observable change in Arthritic Pains. It was assumed that Peak Heart Rate Zone Minutes could produce an observable change in Arthritic Pains for as much as 1 days after the stimulus event.
Predictive Analysis Settings

Data Quantity
504 raw Peak Heart Rate Zone Minutes measurements with 708 changes spanning 1465 days from 2015-03-30 to 2019-04-03 were used in this analysis. 173 raw Arthritic Pains measurements with 44 changes spanning 296 days from 2018-07-21 to 2019-05-13 were used in this analysis.

Data Sources

Peak Heart Rate Zone Minutes data was primarily collected using Fitbit. Fitbit makes activity tracking easy and automatic.

Arthritic Pains 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 very weakly negative relationship between Peak Heart Rate Zone and Arthritic Pains

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. 141 paired data points were used in this analysis. Assuming that the relationship is merely coincidental, as the participant independently modifies their Peak Heart Rate Zone 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 Peak Heart Rate Zone and Arthritic Pains 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 Peak Heart Rate Zone
Effect Variable Name Arthritic Pains
Sinn Predictive Coefficient 0.0071
Confidence Level medium
Confidence Interval 0.37669026802954
Forward Pearson Correlation Coefficient -0.008
Critical T Value 1.646
Total Peak Heart Rate Zone Over Previous 24 hours Before ABOVE Average Arthritic Pains 4 minutes
Total Peak Heart Rate Zone Over Previous 24 hours Before BELOW Average Arthritic Pains 4 minutes
Duration of Action 24 hours
Effect Size very weakly negative
Number of Paired Measurements 141
Optimal Pearson Product -3.7695800205956E-5
P Value 0.38394512007979
Statistical Significance 0.88175808901944
Strength of Relationship 0.37669026802954
Study Type individual
Analysis Performed At 2019-05-15

Peak Heart Rate Zone Statistics

Property Value
Variable Name Peak Heart Rate Zone Minutes
Aggregation Method SUM
Analysis Performed At 2019-05-08
Duration of Action 24 hours
Kurtosis 40.542224314301
Maximum Allowed Value 7 days
Mean 2 minutes
Median 0 microseconds
Minimum Allowed Value 0 microseconds
Number of Changes 708
Number of Correlations 715
Number of Measurements 504
Onset Delay 0 seconds
Standard Deviation 8.1542957013979
Unit Minutes
Variable ID 5211911
Variance 66.492538385836

Arthritic Pains Statistics

Property Value
Variable Name Arthritic Pains
Aggregation Method MEAN
Analysis Performed At 2019-05-15
Duration of Action 24 hours
Kurtosis 3.7990573691823
Maximum Allowed Value 5 out of 5
Mean 1.7574 out of 5
Median 1 out of 5
Minimum Allowed Value 1 out of 5
Number of Changes 44
Number of Correlations 220
Number of Measurements 173
Onset Delay 0 seconds
Standard Deviation 1.0559510782885
Unit 1 to 5 Rating
Variable ID 5795361
Variance 1.1150326797386

Tracking Peak Heart Rate Zone

Get Fitbit here and use it to record your Peak Heart Rate Zone. 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 Arthritic Pains

Record your Arthritic Pains 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