Mike P. Sinn
PRINCIPAL INVESTIGATOR
Mike P. Sinn

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For most, Facebook Posts is generally highest after an average of 1.5 out of 5 of Irritability over the previous 24 hours.
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People with higher Irritability usually have lower Facebook Posts
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for Irritability on each day of the week.
This chart shows the typical value recorded for Irritability for each month of the year.
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for Facebook Posts on each day of the week.
This chart shows the typical value recorded for Facebook Posts for each month of the year.

Abstract

Aggregated data from 25 study participants suggests with a medium degree of confidence (p=0.20455417265931, 95% CI -2.127 to 1.977) that Irritability has a very weakly negative predictive relationship (R=-0.07) with Facebook Posts. The highest quartile of Facebook Posts measurements were observed following an average 1.94 out of 5 Irritability. The lowest quartile of Facebook Posts measurements were observed following an average 2.4909472511946 /5 Irritability.

Objective

The objective of this study is to determine the nature of the relationship (if any) between Irritability and Facebook Posts. Additionally, we attempt to determine the Irritability values most likely to produce optimal Facebook Posts values.

Participant Instructions

Record your Irritability daily in the reminder inbox or using the interactive web or mobile notifications.
Record your Facebook Posts daily in the reminder inbox or using the interactive web or mobile notifications.

Design

This study is based on data donated by 25 participants. Thus, the study design is equivalent to the aggregation of 25 separate n=1 observational natural experiments.

Data Analysis

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

Facebook Posts Pre-Processing
Facebook Posts measurement values below 0 event were assumed erroneous and removed. No maximum allowed measurement value was defined for Facebook Posts. It was assumed that any gaps in Facebook Posts data were unrecorded 0 event measurement values.
Facebook Posts Analysis Settings

Predictive Analytics
It was assumed that 0 hours would pass before a change in Irritability would produce an observable change in Facebook Posts. It was assumed that Irritability could produce an observable change in Facebook Posts for as much as 1 days after the stimulus event.
Predictive Analysis Settings

Data Sources

Irritability 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.

Facebook Posts 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 Irritability and Facebook Posts

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. 62 paired data points were used in this analysis. Assuming that the relationship is merely coincidental, as the participant independently modifies their Irritability 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 Irritability and Facebook Posts 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 Irritability
Effect Variable Name Facebook Posts
Sinn Predictive Coefficient 0.031681180634052
Confidence Level medium
Confidence Interval 2.0518169143187
Forward Pearson Correlation Coefficient -0.0747
Critical T Value 1.7264079971008
Average Irritability Over Previous 24 hours Before ABOVE Average Facebook Posts 1.94 out of 5
Average Irritability Over Previous 24 hours Before BELOW Average Facebook Posts 2.4909472511946 out of 5
Duration of Action 24 hours
Effect Size very weakly negative
Number of Paired Measurements 62
Optimal Pearson Product 0.16743099331441
P Value 0.20455417265931
Statistical Significance 0.25539200037718
Strength of Relationship 2.0518169143187
Study Type population
Analysis Performed At 2019-01-29
Number of Participants 25

Irritability Statistics

Property Value
Variable Name Irritability
Aggregation Method MEAN
Analysis Performed At 2019-01-20
Duration of Action 24 hours
Kurtosis 4.4960400745927
Maximum Allowed Value 5 out of 5
Mean 2.5165796968056 out of 5
Median 2.4672470652897 out of 5
Minimum Allowed Value 1 out of 5
Number of Correlations 462
Number of Measurements 48412
Onset Delay 0 seconds
Standard Deviation 0.51216330843249
Unit 1 to 5 Rating
Variable ID 1358
Variance 0.57553481012702

Facebook Posts Statistics

Property Value
Variable Name Facebook Posts
Aggregation Method SUM
Analysis Performed At 2019-01-27
Duration of Action 7 days
Kurtosis 85.903691814345
Mean 0.51188199632653 event
Median 0.1469387755102 event
Minimum Allowed Value 0 event
Number of Correlations 350
Number of Measurements 260487
Onset Delay 0 seconds
Standard Deviation 1.064832628711
Unit Event
Variable ID 1884
Variance 2.4277407729949

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