Is ARIMA model appropriate for this dental research?

[Ivan Balducci]

Hi members.
Please, I have a doubt in my study for doctoral thesis...

Title: "Development of a thermal cycling protocol for dental materials".
Objective: to create a protocol for thermal aging, from measurements that were found in people mouth.

Doubt: What analyses could I use for this variation temperature data?
Experimental unit: six volunteers

Variable: temperature

Context:
In one day there is 16000 data. In 3 days, there is 48000 data for each volunteers.
Then, I have 6 x 48000 = 288.000 temperature values !!!!

more informations

A student of PhD in dentistry did a work to describe an average pattern of temperature (°C) variation in the oral cavity of six volunteers.

She collected oral temperature data (°C) for 3 days, in 6 patients at each 4 of 4 seconds.

The aim is to establish an average pattern of temperature variation, according to the time, temperature variation and the number of changes per day.

The patients have different routines of each others and per day, so, is there any statistical analyses that I can establish a standard protocol with her data?

Basically, she would like to find an answer like as: A person, on average, per day, has three temperature increases of 40°C , which was maintained for 40 seconds, and 3 temperature decreases from 16°C maintained for 40 seconds.

Is ARIMA test appropriate for this study?

TIA
Ivan

[Rich Ulrich]

On Thu, 3 Apr 2014 12:41:08 -0700 (PDT), Ivan Balducci

Post by Ivan Balducci
Hi members.
Please, I have a doubt in my study for doctoral thesis...
Title: "Development of a thermal cycling protocol for dental materials".
Objective: to create a protocol for thermal aging, from measurements that were found in people mouth.
Doubt: What analyses could I use for this variation temperature data?
Experimental unit: six volunteers
Variable: temperature
In one day there is 16000 data. In 3 days, there is 48000 data for each volunteers.
Then, I have 6 x 48000 = 288.000 temperature values !!!!
more informations
A student of PhD in dentistry did a work to describe an average pattern of temperature (°C) variation in the oral cavity of six volunteers.
She collected oral temperature data (°C) for 3 days, in 6 patients at each 4 of 4 seconds.
The aim is to establish an average pattern of temperature variation, according to the time, temperature variation and the number of changes per day.
The patients have different routines of each others and per day, so, is there any statistical analyses that I can establish a standard protocol with her data?
Basically, she would like to find an answer like as: A person, on average, per day, has three temperature increases of 40°C , which was maintained for 40 seconds, and 3 temperature decreases from 16°C maintained for 40 seconds.

I drink hot coffee a lot, and iced drink occasionally, but I
don't think that any sizable temperature increase ever lasts
for 40 seconds. Of course, these days, I have sensitive teeth
and I'm possibly avoiding pain -- but, even granting that teeth
don't cool or warm up instantly, 40 seconds seems to indicate
that someone is in a hurry to finish a large cup.

Is there some reason that 40 seconds has been a magic
number in some literature?

Post by Ivan Balducci
Is ARIMA test appropriate for this study?

At some point, there might be call for ARIMA, but that
seems like a poor starting point.

What do events *look* like? I think you should start by
looking at time-series plots of points, and map them to
macro-events such as eating meals and drinking cold and hot
beverages. Figure out how to characterize an "event" so that
it can be detected by algorith.

One first question is whether the "events" are similar enough
for six people that you can detect and characterize them
by the same algorithm for everyone.

[Ivan Balducci]

Thanks Dr Ulrich for answered it. Now, the student wants to explain something:
So, in dental laboratory studies we use to aging the specimens, thermal variations. We put the specimens, for example, in cold water for 40 seconds and then in hot water for more 40 seconds.
The example wrote before, it´s only to become easier the answer I want to receive.
I want to know more about the algorith in this case.
Thank you!



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Post by Ivan Balducci
Hi members.
Please, I have a doubt in my study for doctoral thesis...
Title: "Development of a thermal cycling protocol for dental materials".
Objective: to create a protocol for thermal aging, from measurements that were found in people mouth.
Doubt: What analyses could I use for this variation temperature data?
Experimental unit: six volunteers
Variable: temperature
In one day there is 16000 data. In 3 days, there is 48000 data for each volunteers.
Then, I have 6 x 48000 = 288.000 temperature values !!!!
more informations
A student of PhD in dentistry did a work to describe an average pattern of temperature (°C) variation in the oral cavity of six volunteers.
She collected oral temperature data (°C) for 3 days, in 6 patients at each 4 of 4 seconds.
The aim is to establish an average pattern of temperature variation, according to the time, temperature variation and the number of changes per day.
The patients have different routines of each others and per day, so, is there any statistical analyses that I can establish a standard protocol with her data?
Basically, she would like to find an answer like as: A person, on average, per day, has three temperature increases of 40°C , which was maintained for 40 seconds, and 3 temperature decreases from 16°C maintained for 40 seconds.
Is ARIMA test appropriate for this study?
TIA
Ivan

[Rich Ulrich]

On Fri, 4 Apr 2014 05:04:54 -0700 (PDT), Ivan Balducci

Post by Ivan Balducci
So, in dental laboratory studies we use to aging the specimens, thermal variations. We put the specimens, for example, in cold water for 40 seconds and then in hot water for more 40 seconds.
The example wrote before, it´s only to become easier the answer I want to receive.
I want to know more about the algorith in this case.
Thank you!

Ivan,
Are you asking another question here?

It is interesting, that the "40 seconds" is a time frame that
arises from a lab-bench sort of experiment. If the same
timing *works* in the human volunteer data, that would
be convenient. But I would not start my examination of
the human data there unless it has been validated and has
already become a standard.

My mention of "algorithm" was to describe what you should
hope to end up with, from examining the scattergrams
and testing out various things to measure.