- #1

bhartish

- 26

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**urgent reply needed**

Can we use partial means as a predictor for the response while fitting a regression line or curve?.

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- Thread starter bhartish
- Start date

In summary, the conversation discusses the use of partial means as a predictor for the response in fitting a regression line or curve. The concept of partial means is explained as weighted averages of derivatives of regression functions. The answer to the original question is yes, as long as it is appropriate. The importance of posting questions early and avoiding words like "urgent" and "ASAP" is also mentioned.

- #1

bhartish

- 26

- 0

Can we use partial means as a predictor for the response while fitting a regression line or curve?.

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- #2

chiro

Science Advisor

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bhartish said:Can we use partial means as a predictor for the response while fitting a regression line or curve?.

Hey bhartish and welcome to the forums.

What is a partial mean? Is this just a mean of a subset of your actual data? I've never come across this term before.

- #3

SW VandeCarr

- 2,199

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chiro said:Hey bhartish and welcome to the forums.

What is a partial mean? Is this just a mean of a subset of your actual data? I've never come across this term before.

It's used in econometrics and involves the weighted averages of derivatives of regression functions. They're defined in section 2.2 of the link.

http://www.economics.harvard.edu/faculty/imbens/files/ir.pdf

The answer to the OPs question seems to be yes, where it's appropriate.

Last edited by a moderator:

- #4

turbo

Gold Member

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BTW, "urgent" and "needed" along with "ASAP" are bound to get your posts ignored. There are plenty of smart folks here that will help you, but they'll be turned off if you wait until the last minute and then demand help. If you are in need, post your questions early so members can help you, and you can get clarification along the way. Just a suggestion.

- #5

SW VandeCarr

- 2,199

- 81

turbo said:

Yes. Ditto for exclamation marks !

The purpose of using partial means to predict a regression line is to determine the relationship between two variables by estimating the slope and intercept of the regression line. This can be helpful in understanding the impact of one variable on the other and making predictions based on the given data.

Partial means are calculated by taking the average of the values of one variable while holding the other variable constant. This allows for the calculation of the slope and intercept of the regression line, which can then be used to make predictions.

Partial means can provide a good estimate of the regression line, but they may not always accurately predict it. This is because the relationship between variables may not be linear and there may be other factors that influence the data.

One limitation of using partial means is that it assumes a linear relationship between the variables. It also does not take into account any other variables that may affect the data, leading to potential errors in the predictions. Additionally, the accuracy of the predictions may depend on the amount and quality of the data available.

The accuracy of partial means predictions can be improved by using a larger and more diverse dataset, as well as considering other variables that may affect the relationship between the two variables. Additionally, using more advanced statistical techniques and conducting further analysis can also help improve the accuracy of the predictions.

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