This individual's Tiredness / Fatigue is generally lowest after a daily total of 180 milligrams of Remeron intake over the previous 7 days.
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Blue represents the sum of Remeron intake over the previous 7 days
An increase in 7 days cumulative Remeron intake is usually followed by an decrease in Tiredness / Fatigue. (R = -0.15)
Typical values for Tiredness / Fatigue following a given amount of Remeron intake over the previous 7 days.
Typical Remeron intake seen over the previous 7 days preceding the given Tiredness / Fatigue value.
Correlation between outcome and aggregated predictor measurements over given number of days
Peak correlation suggests the delay between predictor and observable outcome
This chart shows how your Remeron changes over time.
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for Remeron on each day of the week.
This chart shows the typical value recorded for Remeron for each month of the year.
This chart shows how your Tiredness / Fatigue changes over time.
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for Tiredness / Fatigue on each day of the week.
This chart shows the typical value recorded for Tiredness / Fatigue for each month of the year.

Abstract

This individual's Tiredness / Fatigue is generally 15.59% lower than normal after 180 milligrams Remeron per 7 days. This individual's data suggests with a high degree of confidence (p=1.7247074619199E-15, 95% CI -0.302 to 0.002) that Remeron has a weakly negative predictive relationship (R=-0.15) with Tiredness / Fatigue. The highest quartile of Tiredness / Fatigue measurements were observed following an average 116.66 milligrams Remeron per day. The lowest quartile of Tiredness / Fatigue measurements were observed following an average 154.58620689655 mg Remeron per day.Tiredness/ Fatigue is generally 15.59% lower than normal after a total of 154.58620689655 milligrams of Remeron intake over the previous 7 days. Tiredness / Fatigue is generally 19.54% higher after a total of 116.66 milligrams of Remeron intake over the previous 7 days.

Objective

The objective of this study is to determine the nature of the relationship (if any) between Remeron and Tiredness / Fatigue. Additionally, we attempt to determine the Remeron values most likely to produce optimal Tiredness / Fatigue values.

Participant Instructions

Record your Remeron daily in the reminder inbox or using the interactive web or mobile notifications.
Record your Tiredness / Fatigue 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

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

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

Predictive Analytics
It was assumed that 0 hours would pass before a change in Remeron would produce an observable change in Tiredness / Fatigue. It was assumed that Remeron could produce an observable change in Tiredness / Fatigue for as much as 7 days after the stimulus event.
Predictive Analysis Settings

Data Quantity
89 raw Remeron measurements with 216 changes spanning 2356 days from 2013-01-12 to 2019-06-27 were used in this analysis. 546 raw Tiredness / Fatigue measurements with 206 changes spanning 1824 days from 2014-06-28 to 2019-06-27 were used in this analysis.

Data Sources

Remeron 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.

Tiredness / Fatigue 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 negative relationship between Remeron intake and Tiredness / Fatigue

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. 471 paired data points were used in this analysis. Assuming that the relationship is merely coincidental, as the participant independently modifies their Remeron intake 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 Remeron intake and Tiredness / Fatigue 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 Remeron intake
Effect Variable Name Tiredness / Fatigue
Sinn Predictive Coefficient 0.1469
Confidence Level high
Confidence Interval 0.15216908563037
Forward Pearson Correlation Coefficient -0.15
Critical T Value 1.646
Total Remeron intake Over Previous 7 days Before ABOVE Average Tiredness / Fatigue 116.66 milligrams
Total Remeron intake Over Previous 7 days Before BELOW Average Tiredness / Fatigue 154.586 milligrams
Duration of Action 7 days
Effect Size weakly negative
Number of Paired Measurements 471
Optimal Pearson Product 0.044789377585154
P Value 1.7247074619199E-15
Statistical Significance 0.97907182573215
Strength of Relationship 0.15216908563037
Study Type individual
Analysis Performed At 2019-06-28

Remeron Statistics

Property Value
Variable Name Remeron
Aggregation Method SUM
Analysis Performed At 2019-06-28
Duration of Action 7 days
Kurtosis 30.113874244533
Mean 10.478 milligrams
Median 0 milligrams
Minimum Allowed Value 0 milligrams
Number of Changes 216
Number of Correlations 142
Number of Measurements 89
Onset Delay 0 seconds
Standard Deviation 17.473772313353
Unit Milligrams
UPC 863694000011
Variable ID 1431
Variance 305.3327188589

Tiredness / Fatigue Statistics

Property Value
Variable Name Tiredness / Fatigue
Aggregation Method MEAN
Analysis Performed At 2019-06-28
Duration of Action 7 days
Kurtosis 2.6797269783922
Maximum Allowed Value 5 out of 5
Mean 2.1262 out of 5
Median 2 out of 5
Minimum Allowed Value 1 out of 5
Number of Changes 206
Number of Correlations 848
Number of Measurements 546
Onset Delay 0 seconds
Standard Deviation 1.02461275319
Unit 1 to 5 Rating
UPC 635797687433
Variable ID 87760
Variance 1.0498312939996

Tracking Remeron

Record your Remeron daily in the reminder inbox or using the interactive web or mobile notifications.

Tracking Tiredness / Fatigue

Record your Tiredness / Fatigue 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