It's appropriate whenever the elements you're pooling together are homogeneous with respect to the parameters you're estimating. Specifically, this means that, if the model underlying each component is the same, with the same parameter values, then it is fine to pool the data.
Full Answer
Is it possible to test the poolability of monthly data?
To add to what Macro said, You can test the assumption of the poolability of the monthly data based on time series analysis. But it would require a lot more monthly data. With the time series analysis you could look for a season trend of a yearly cycle.
Is it okay to pool data in a regression model?
Specifically, this means that, if the model underlying each component is the same, with the same parameter values, then it is fine to pool the data. Otherwise, it's tantamount to leaving an important interaction out of a regression model which can cause misleading inferences.
Can the standard deviation of the proportion be estimated by pooling?
So, I would say this means the standard deviation of the proportion cannot be estimated by pooling in this way (since, there are two proportions that are assumed to be different!) Pooling the standard deviation is possible in the case where the proportions are equal in the Null Hypothesis.
How many Americans go swimming in Singapore?
More than 7 million residents and visitors went to swimming pools in Singapore in 2017, according to Singapore in Figures 2018 , a report conducted by the Department of Statistics in Singapore. Although these swimming stats show many Americans haven't actually taken official lessons, swimming is one of the most popular sports in the U.S.
Can you test the poolability of the monthly data based on time series analysis?
Is it okay to pool data?
Can you pool ads and total revenue?
About this website
Why do you pool in statistics?
In statistics, “pooling” describes the practice of gathering together small sets of data that are assumed to have the same value of a characteristic (e.g., a mean) and using the combined larger set (the “pool”) to obtain a more precise estimate of that characteristic.
When can you use pool data?
Pooling is on the basis of similarity. For two sets of data to be pooled there should be similarity between them often in terms of their variances. It means their variances should not be significantly different. Test for equality of two variances is usually based on the F distribution.
What is the advantage of pooling data?
Benefits of pooling individual subject data include enhanced statistical power, the ability to compare outcomes and validate models across sites or settings, and opportunities to develop new measures.
What is pooled data with example?
Pooled data is a mixture of time series data and cross-section data. One example is GNP per capita of all European countries over ten years. Panel, longitudinal or micropanel data is a type that is pooled data of nature.
What is a pooled data set?
What is data pooling? Data pooling is a process where data sets coming from different sources are combined. This can mean two things. First, that multiple datasets containing information on many patients from different countries or from different institutions is merged into one data file.
What is pooling in information retrieval?
The pooling method consists of optimizing the relevance assessment process by pooling the documents retrieved by different search engines following a particular pooling strategy. The most common one consists on pooling the top d documents of each run.
What are the disadvantages of pooling?
Disadvantages of pool organizationLack of stability: In a pooling arrangement member units enjoy considerable autonomy and contracts cannot be enforced. ... Exploitation of consumers: Pools lead to monopoly situations and it is common knowledge that consumers are exploited in monopolies.More items...
What are the benefits of pooling and sharing information?
Data sharing encourages more connection and collaboration between researchers, which can result in important new findings within the field. In a time of reduced monetary investment for science and research, data sharing is more efficient because it allows researchers to share resources.
What is pool analysis?
A pooled analysis is a statistical technique for combining the results of multiple epidemiological studies. It is one of three types of literature reviews frequently used in epidemiology, along with meta-analysis and traditional narrative reviews. Pooled analyses may be either retrospective or prospective.
When to use pooled OLS vs fixed effects?
According to Wooldridge (2010), pooled OLS is employed when you select a different sample for each year/month/period of the panel data. Fixed effects or random effects are employed when you are going to observe the same sample of individuals/countries/states/cities/etc.
What is the difference between pooled data and panel data?
Pooled data occur when we have a “time series of cross sections,” but the observations in each cross section do not necessarily refer to the same unit. Panel data refers to samples of the same cross-sectional units observed at multiple points in time.
How does a data pool work?
A data pool is a centralized repository of data where trading partners (retailers, distributors, or suppliers) can obtain, maintain, and exchange information about products in a standard format. Suppliers can upload data to a data pool, which retailers receive through their data pool.
What is a data pool vs data lake?
Data Lake and Data Pool differ not only in size, but usage. Data Lake is large and has many users. A Data Pool is large but not the size of a data Lake and has many distinct users viewing same data. The lake is not shared data, but allows for many users not sharing data.
What are data Lakes and data pools?
A data pool is an independent, isolated micro-data lake. A data lake includes at least one, but ideally many data pools that belong to the same organization, and are managed independently (they can even run on different cloud vendors!).
What exactly does it mean to 'pool data'? - Cross Validated
Yes, your examples are correct. The Oxford English Dictionary defines pool as:. pool, v. (puːl) 1.1 trans. To throw into a common stock or fund to be distributed according to agreement; to combine (capital or interests) for the common benefit; spec. of competing railway companies, etc.:
To pool or not to pool - StatLit.Org
2013-Knapp-To-pool-or-not-to-pool.doc Page 2 Satterthwaite test or the Behrens-Fisher test. It is the default t test in Minitab. If you want the pooled test you have to explicitly request it.]
statistics - In what situations should I use and not use a pooled ...
My intuition is: in this question you are testing the difference between proportions. Your null hypothesis assumption is that the proportions are not the same. So, I would say this means the standard deviation of the proportion cannot be estimated by pooling in this way (since, there are two proportions that are assumed to be different!)
Diving into Best Practices for Pooling Clinical Trial Data
If you’ve worked with a client drug development team approaching submission for approval, it’s likely you’ve heard discussions like this: Team member 1:
7.4 - Sample Pooling | STAT 555
Printer-friendly version. We say that samples are pooled when units that might be measured separately are processed together in such a way that the separate measurements can no longer be determined.
When to Calculate the Pooled Variance
When we want to compare two population means, there are two statistical tests we could potentially use:
Example of Calculating the Pooled Variance
Suppose we want to know whether or not the mean weight between two different species of turtles is equal. To test this, we collect a random sample of turtles from each population with the following information:
What temperature should a pool be?
The temperature of a swimming pool should be between 77 and 82 degrees Fahrenheit (25 to 28 degrees Celsius), according to FINA.
How many times do kids swim?
About 36% of children 7 to 17 years old swim at least six times each year. About 15% of adults swim at least six times each year. There are more than 3,100 professional swimming clubs, which include more than 400,000 members, according to USA Swimming , the national governing body for swimming in the country.
How many people swim in Australia?
Roughly 6 million adults in Australia (about 23% of the population) swim, making it the country's No. 1 sport, according to a March 2018 issue of the Journal of t he Australian Swimming Coaches & Teachers Association & Swim Australia . About 4 million adults in England (about 6% of the population) went swimming between May 2019 and 2020, ...
How many people in England swim in 2020?
About 4 million adults in England (about 6% of the population) went swimming between May 2019 and 2020, which is a decrease of 644,000 participants from the previous year, according to Sport England's Active Lives Adult Survey May 2019/2020 report.
How many people are paralyzed by diving?
Globally, about 3,000 people are fully or partially paralyzed after breaking their necks swimming. Most of these deaths are a result of diving in shallow water, according to the International Life Saving Foundation.
Does swimming reduce the risk of heart disease?
After tracking more than 80,000 adults for more than 20 years, researchers found that swimming was associated with a reduced risk of dying from heart disease in a May 2017 British Journal of Sports Medicine study. Adults who swam had a 28% lower risk of all-cause death.
Is swimming good for you?
Aside from instantly cooling you down on a hot day, the health benefits of swimming include improving your cardiovascular endurance, promoting weight loss and protecting your joints.
What is the true significance level of a pooled test?
Then the true significance level of the pooled test is almost 30% for the 100,000 simulated datasets, where one expects 5%.
What is the significance level of a test intended to be at 5%?
For moderate n 1 and n 2, the significance level of a test intended to be at the 5% level has actual significance level very nearly 5%. Also, the power of the Welch test is not noticeably smaller than for a corresponding pooled two-sample t test. With little or no penalty attached to the Welch test, it should almost always be used instead of the pooled test.
How many reputations do you need to answer a highly active question?
Highly active question. Earn 10 reputation (not counting the association bonus) in order to answer this question. The reputation requirement helps protect this question from spam and non-answer activity.
What is the null hypothesis assumption for the standard deviation of the proportion?
My intuition is: in this question you are testing the difference between proportions. Your null hypothesis assumption is that the proportions are not the same . So, I would say this means the standard deviation of the proportion cannot be estimated by pooling in this way (since, there are two proportions that are assumed to be different!)
Is pooling standard deviation possible?
Pooling the standard deviation is possible in the case where the proportions are equal in the Null Hypothesis. Pooling is then permitted (and offers more accuracy), because of the assumption that the Null Hypothesis is true and (therefore) that the proportions are equal - so your assumption is that there is only one true proportion that applies to both samples. In that case, p 1 − p 2 = 0, we treat the two samples effectively as though they come from the same population.
What is pooled standard deviation?
A pooled standard deviation is simply a weighted average of standard deviations from two or more independent groups. In statistics it appears most often in the two sample t-test, which is used to test whether or not the means of two populations are equal.
Is pooled standard deviation weighted?
This should make sense considering the pooled standard deviation is just a weighted average between the two groups.
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Can you test the poolability of the monthly data based on time series analysis?
1. To add to what Macro said, You can test the assumption of the poolability of the monthly data based on time series analysis. But it would require a lot more monthly data. With the time series analysis you could look for a season trend of a yearly cycle.
Is it okay to pool data?
It's appropriate whenever the elements you're pooling together are homogeneous with respect to the parameters you're estimating. Specifically, this means that, if the model underlying each component is the same, with the same parameter values, then it is fine to pool the data. Otherwise, it's tantamount to leaving an important interaction out of a regression model which can cause misleading inferences.
Can you pool ads and total revenue?
If the relationship between $ spent on tv ads and total sales revenue is the same across months, then it is OK to pool them together and ignore the month altogether. But, if the effect does depend on month, then you should potentially include interactions that allow the slope and intercept to vary by month. Failing to stratify your parameter estimates by month when they truly should be can cause misleading estimates of the variable effect (see here for a toy example).
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