For most, Irritability is generally lowest after a daily total of 20 milligrams of Buspirone intake over the previous 7 days.


Abstract
Aggregated data from 5 study participants suggests with a low degree of confidence (p=0.20912459849692, 95% CI 0.678 to 0.201) that Buspirone (mg) has a weakly negative predictive relationship (R=0.24) with Irritability. The highest quartile of Irritability measurements were observed following an average 38.26 milligrams Buspirone (mg) per day. The lowest quartile of Irritability measurements were observed following an average 28.238095238095 mg Buspirone (mg) per day.
Objective
The objective of this study is to determine the nature of the relationship (if any) between Buspirone (mg) and Irritability. Additionally, we attempt to determine the Buspirone (mg) values most likely to produce optimal Irritability values.
Participant Instructions
Record your Buspirone daily in the reminder inbox or using the interactive web or mobile notifications.
Record your Irritability daily in the reminder inbox or using the interactive web or mobile notifications.
Record your Irritability daily in the reminder inbox or using the interactive web or mobile notifications.
Design
This study is based on data donated by 5 participants. Thus, the study design is equivalent to the aggregation of 5 separate n=1 observational natural experiments.
Data Analysis
Buspirone PreProcessing
Buspirone measurement values below 0 milligrams were assumed erroneous and removed. No maximum allowed measurement value was defined for Buspirone. It was assumed that any gaps in Buspirone data were unrecorded 0 milligrams measurement values.
Irritability PreProcessing
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.
Predictive Analytics
It was assumed that 0.5 hours would pass before a change in Buspirone (mg) would produce an observable change in Irritability. It was assumed that Buspirone (mg) could produce an observable change in Irritability for as much as 7 days after the stimulus event.
Buspirone measurement values below 0 milligrams were assumed erroneous and removed. No maximum allowed measurement value was defined for Buspirone. It was assumed that any gaps in Buspirone data were unrecorded 0 milligrams measurement values.

Irritability PreProcessing
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.

Predictive Analytics
It was assumed that 0.5 hours would pass before a change in Buspirone (mg) would produce an observable change in Irritability. It was assumed that Buspirone (mg) could produce an observable change in Irritability for as much as 7 days after the stimulus event.

Data Sources
Buspirone (mg) 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.
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.
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.
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 nonexistent 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 Buspirone intake and Irritability
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. 54 paired data points were used in this analysis. Assuming that the relationship is merely coincidental, as the participant independently modifies their Buspirone 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 timeprecedence 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 biochemical 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 Buspirone intake and Irritability 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.
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 Buspirone intake and Irritability
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. 54 paired data points were used in this analysis. Assuming that the relationship is merely coincidental, as the participant independently modifies their Buspirone 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 timeprecedence 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 biochemical 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 Buspirone intake and Irritability 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  Buspirone intake 
Effect Variable Name  Irritability 
Sinn Predictive Coefficient  0.037924978197539 
Confidence Level  low 
Confidence Interval  0.4392614922935 
Forward Pearson Correlation Coefficient  0.2384 
Critical T Value  1.6936 
Total Buspirone intake Over Previous 7 days Before ABOVE Average Irritability  38.26 milligrams 
Total Buspirone intake Over Previous 7 days Before BELOW Average Irritability  28.238095238095 milligrams 
Duration of Action  7 days 
Effect Size  weakly negative 
Number of Paired Measurements  54 
Optimal Pearson Product  0.72232949170663 
P Value  0.20912459849692 
Statistical Significance  0.199640000402 
Strength of Relationship  0.4392614922935 
Study Type  population 
Analysis Performed At  20190202 
Number of Participants  5 
Buspirone Statistics
Property  Value 

Variable Name  Buspirone (mg) 
Aggregation Method  SUM 
Analysis Performed At  20181222 
Duration of Action  7 days 
Kurtosis  23.961641448213 
Mean  26.533854166667 milligrams 
Median  24.166666666667 milligrams 
Minimum Allowed Value  0 milligrams 
Number of Correlations  24 
Number of Measurements  375 
Onset Delay  30 minutes 
Standard Deviation  5.0422816599857 
Unit  Milligrams 
UPC  091037446671 
Variable ID  592301 
Variance  50.841471434876 
Irritability Statistics
Property  Value 

Variable Name  Irritability 
Aggregation Method  MEAN 
Analysis Performed At  20190130 
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 
Principal Investigator  Mike Sinn