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This individual's Guiltiness is generally lowest after an average of 76 millimeters merc of Blood Pressure over the previous 7 days.
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Blue represents the mean of Blood Pressure over the previous 7 days
An increase in 7 days cumulative Blood Pressure is usually followed by an increase in Guiltiness. (R = 0.269)
Typical values for Guiltiness following a given amount of Blood Pressure over the previous 7 days.
Typical Blood Pressure seen over the previous 7 days preceding the given Guiltiness value.
This chart shows how your Blood Pressure changes over time.
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for Blood Pressure on each day of the week.
This chart shows the typical value recorded for Blood Pressure for each month of the year.
This chart shows how your Guiltiness changes over time.
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for Guiltiness on each day of the week.
This chart shows the typical value recorded for Guiltiness for each month of the year.

Abstract

This individual's Guiltiness is generally 10% lower than normal after 76.15 millimeters merc Blood Pressure (Diastolic - Bottom Number) per 7 days. This individual's data suggests with a high degree of confidence (p=0.00022149047464219, 95% CI 0.08 to 0.458) that Blood Pressure (Diastolic - Bottom Number) has a weakly positive predictive relationship (R=0.27) with Guiltiness. The highest quartile of Guiltiness measurements were observed following an average 78.75 millimeters merc Blood Pressure (Diastolic - Bottom Number). The lowest quartile of Guiltiness measurements were observed following an average 76.261928104575 mmHg Blood Pressure (Diastolic - Bottom Number).Guiltiness is generally 10% lower than normal after an average of 76.261928104575 millimeters merc of Blood Pressure (Diastolic - Bottom Number) over the previous 7 days. Guiltiness is generally 9% higher after an average of 78.75 millimeters merc of Blood Pressure (Diastolic - Bottom Number) over the previous 7 days.

Objective

The objective of this study is to determine the nature of the relationship (if any) between Blood Pressure and Guiltiness. Additionally, we attempt to determine the Blood Pressure (Diastolic - Bottom Number) values most likely to produce optimal Guiltiness values.

Participant Instructions

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

Blood Pressure Pre-Processing
Blood Pressure measurement values below 0 millimeters merc were assumed erroneous and removed. No maximum allowed measurement value was defined for Blood Pressure. No missing data filling value was defined for Blood Pressure so any gaps in data were just not analyzed instead of assuming zero values for those times.
Blood Pressure Analysis Settings

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

Predictive Analytics
It was assumed that 0 hours would pass before a change in Blood Pressure (Diastolic - Bottom Number) would produce an observable change in Guiltiness. It was assumed that Blood Pressure (Diastolic - Bottom Number) could produce an observable change in Guiltiness for as much as 7 days after the stimulus event.
Predictive Analysis Settings

Data Quantity
1515 raw Blood Pressure (Diastolic - Bottom Number) measurements with 347 changes spanning 2074 days from 2013-03-05 to 2018-11-09 were used in this analysis. 2793 raw Guiltiness measurements with 661 changes spanning 1961 days from 2013-11-17 to 2019-04-01 were used in this analysis.

Data Sources

Blood Pressure (Diastolic - Bottom Number) data was primarily collected using Withings. Withings creates smart products and apps to take care of yourself and your loved ones in a new and easy way. Discover the Withings Pulse, Wi-Fi Body Scale, and Blood Pressure Monitor.

Guiltiness 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 weakly positive relationship between Blood Pressure (Diastolic - Bottom Number) and Guiltiness

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. 187 paired data points were used in this analysis. Assuming that the relationship is merely coincidental, as the participant independently modifies their Blood Pressure (Diastolic - Bottom Number) 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 Blood Pressure (Diastolic - Bottom Number) and Guiltiness 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 Blood Pressure (Diastolic - Bottom Number)
Effect Variable Name Guiltiness
Sinn Predictive Coefficient 0.3018
Confidence Level high
Confidence Interval 0.1886865310783
Forward Pearson Correlation Coefficient 0.269
Critical T Value 1.646
Average Blood Pressure ( Diastolic - Bottom Number) Over Previous 7 days Before ABOVE Average Guiltiness 78.75 millimeters merc
Average Blood Pressure ( Diastolic - Bottom Number) Over Previous 7 days Before BELOW Average Guiltiness 76.262 millimeters merc
Duration of Action 7 days
Effect Size weakly positive
Number of Paired Measurements 187
Optimal Pearson Product 0.13541691864478
P Value 0.00022149047464219
Statistical Significance 0.9958
Strength of Relationship 0.1886865310783
Study Type individual
Analysis Performed At 2019-04-04

Blood Pressure Statistics

Property Value
Variable Name Blood Pressure (Diastolic - Bottom Number)
Aggregation Method MEAN
Analysis Performed At 2019-01-29
Duration of Action 7 days
Kurtosis 3.0902415726782
Mean 79.585 millimeters merc
Median 79.5 millimeters merc
Minimum Allowed Value 0 millimeters merc
Number of Changes 347
Number of Correlations 2630
Number of Measurements 1515
Onset Delay 0 seconds
Standard Deviation 6.3392479360027
Unit Millimeters Merc
Variable ID 5554981
Variance 40.186064394114

Guiltiness Statistics

Property Value
Variable Name Guiltiness
Aggregation Method MEAN
Analysis Performed At 2019-04-01
Duration of Action 24 hours
Kurtosis 3.1224153723756
Maximum Allowed Value 5 out of 5
Mean 2.1627 out of 5
Median 2 out of 5
Minimum Allowed Value 1 out of 5
Number of Changes 661
Number of Correlations 5379
Number of Measurements 2793
Onset Delay 0 seconds
Standard Deviation 0.92130141512025
Unit 1 to 5 Rating
Variable ID 1335
Variance 0.84879629750257

Tracking Blood Pressure

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

Tracking Guiltiness

Record your Guiltiness 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