This individual's Overall Mood is generally 3.1% higher after 56.5 tablets Creatine over the previous 21 days.
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Blue represents the sum of Creatine over the previous 21 days
An increase in 21 days cumulative Creatine is usually followed by an increase in Overall Mood. (R = 0.101)
Typical values for Overall Mood following a given amount of Creatine over the previous 21 days.
Typical Creatine seen over the previous 21 days preceding the given Overall Mood 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 Creatine (tablets) changes over time.
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for Creatine (tablets) on each day of the week.
This chart shows the typical value recorded for Creatine (tablets) for each month of the year.
This chart shows how Overall Mood changes over time.
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for Overall Mood on each day of the week.
This chart shows the typical value recorded for Overall Mood for each month of the year.

Abstract

I couldn't determine the relationship yet because value_predicting_high_outcome: 23.75 is greater than maximum value:20 of default unit: tablets for correlation of user for cause: Creatine (tablets) and effect: Overall Mood
I generally need a month of data and 30 measurements in order to perform an analysis.
54 raw Creatine (tablets) measurements with 30 changes spanning 210 days from 2013-09-18 to 2014-04-16 were used in this analysis.
14182 raw Overall Mood measurements with 1273 changes spanning 2665 days from 2012-05-06 to 2019-08-22 were used in this analysis.
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Objective

The objective of this study is to determine the nature of the relationship (if any) between Creatine and Overall Mood. Additionally, we attempt to determine the Creatine (tablets) values most likely to produce optimal Overall Mood values.

Participant Instructions

Record your Creatine (tablets) daily in the reminder inbox or using the interactive web or mobile notifications.
Record your Overall Mood 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

Creatine (tablets) Pre-Processing
Creatine (tablets) measurement values below 0 tablets were assumed erroneous and removed. Creatine (tablets) measurement values above 20 tablets were assumed erroneous and removed. It was assumed that any gaps in Creatine (tablets) data were unrecorded 0 tablets measurement values.
Creatine (tablets) Analysis Settings

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

Predictive Analytics
It was assumed that 0.5 hours would pass before a change in Creatine (tablets) would produce an observable change in Overall Mood. It was assumed that Creatine (tablets) could produce an observable change in Overall Mood for as much as 21 days after the stimulus event.
Predictive Analysis Settings

Data Quantity
54 raw Creatine (tablets) measurements with 30 changes spanning 210 days from 2013-09-18 to 2014-04-16 were used in this analysis. 14182 raw Overall Mood measurements with 1273 changes spanning 2665 days from 2012-05-06 to 2019-08-22 were used in this analysis.

Statistical Significance

Using a two-tailed t-test with alpha = 0.05, it was determined that the change in Overall Mood is statistically significant at 95% confidence interval. After treatment, a 3.1% increase (0.077529334431881 out of 5) from the mean baseline 2.504785344108 out of 5 was observed. The relative standard deviation at baseline was 20.6%. The observed change was 0.14993508797131 times the standard deviation. A common rule of thumb considers a change greater than twice the baseline standard deviation on two separate pre-post experiments may be considered significant. This occurrence would may have only a 5% likelihood of resulting from random fluctuation (a p-value

Data Sources

Creatine (tablets) 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.

Overall Mood 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

The accuracy of this study may be limited by the fact that value_predicting_high_outcome: 23.75 is greater than maximum value:20 of default unit: tablets for correlation of user for cause: Creatine (tablets) and effect: Overall Mood. A greater amount of data and more variance in the data would help to resolve this issue.
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 Creatine and Overall Mood

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. 260 paired data points were used in this analysis. Assuming that the relationship is merely coincidental, as the participant independently modifies their Creatine 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 2 feel that any relationship observed between Creatine and Overall Mood 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 Creatine
Effect Variable Name Overall Mood
Sinn Predictive Coefficient 0.0906
Confidence Level high
Confidence Interval 0.083710539019597
Forward Pearson Predictive Coefficient 0.101
Critical T Value 1.646
Total Creatine Over Previous 21 days Before ABOVE Average Overall Mood 23.75 tablets
Total Creatine Over Previous 21 days Before BELOW Average Overall Mood 20.863 tablets
Duration of Action 21 days
Effect Size weakly positive
Number of Paired Measurements 260
Optimal Pearson Product 0.0083673622807311
P Value 0.0049025825181545
Statistical Significance 0.7389
Strength of Relationship 0.083710539019597
Study Type individual
Analysis Performed At 2019-08-13
Number of Pairs 260
Number of Raw Predictor Measurements ( Including Tags, Joins, and Children) 54
Baseline Relative Standard Deviation of Outcome Measurements 20.6
Experiment Duration (days) 291
Number of Raw Outcome Measurements 14145
Z Score 0.14993508797131
Last Analysis 2019-08-13
Experiment Began 2013-08-19 16:03:00
Experiment Ended 2014-06-06 16:30:00
P Value 0.0049025825181545
Predictor Category Treatments
Duration of Action (h) 504
Onset Delay (h) 0.5
Significance 0.7389
Outcome Relative Standard Deviation at Baseline 20.6
Outcome Standard Deviation at Baseline 0.51708599688632/5
Outcome Mean at Baseline 2.504785344108/5
Average Followup Change From Baseline 3.1&
Average Absolute Followup Change From Baseline 2.5823146785399/5
Z- Score 0.14993508797131
Average Predictor Treatment Value 56.5tablets over 21 days

Creatine (tablets) Statistics

Property Value
Variable Name Creatine (tablets)
Aggregation Method SUM
Analysis Performed At 2019-08-22
Duration of Action 21 days
Kurtosis 49.872647342991
Maximum Allowed Value 20 serving
Mean 0.116 serving
Median 0 serving
Minimum Allowed Value 0 serving
Number of Changes 30
Number of Correlations 147
Number of Measurements 54
Onset Delay 30 minutes
Standard Deviation 0.8248857536153
Unit Serving
UPC 748927023855
Variable ID 108482
Variance 0.68043650651747

Overall Mood Statistics

Property Value
Variable Name Overall Mood
Aggregation Method MEAN
Analysis Performed At 2019-08-22
Duration of Action 24 hours
Kurtosis 6.8592239252433
Maximum Allowed Value 5 out of 5
Mean 2.9065 out of 5
Median 3 out of 5
Minimum Allowed Value 1 out of 5
Number of Changes 1273
Number of Correlations 4592
Number of Measurements 14182
Onset Delay 0 seconds
Standard Deviation 0.52145727417909
Unit 1 to 5 Rating
UPC 767674073845
Variable ID 1398
Variance 0.27191768879429

Tracking Creatine (tablets)

Record your Creatine (tablets) daily in the reminder inbox or using the interactive web or mobile notifications.

Tracking Overall Mood

Record your Overall Mood 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