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Jun 8, 2020 3:05 AM
(1062 views)

A situation that is frequently encountered in field experiments is where there are two crossed blocking factors e.g. "day" and "time in the day" e.g. 4 different time intervals in a day. This is a so called row-column experiment. Suppose one has to check 7 effects, how can this row-column DOE set up with the custom designer in JMP?

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Use two blocking factors:

Here is the JSL code to make this illustrative example:

```
DOE(
Custom Design,
{Add Response( Maximize, "Y", ., ., . ), Add Factor( Blocking, 8, "Day" ),
Add Factor( Blocking, 2, "Time of Day" ),
Add Factor( Continuous, -1, 1, "X3", 0 ),
Add Factor( Continuous, -1, 1, "X4", 0 ), Set Random Seed( 353 ),
Add Term( {1, 0} ), Add Term( {3, 1} ), Add Term( {4, 1} ), Add Term( {1, 1} ),
Add Term( {2, 1} ), Add Alias Term( {3, 1}, {4, 1} ), Set Sample Size( 32 ),
Simulate Responses( 0 ), Save X Matrix( 0 )}
);
```

Learn it once, use it forever!

18 REPLIES 18

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Use two blocking factors:

Here is the JSL code to make this illustrative example:

```
DOE(
Custom Design,
{Add Response( Maximize, "Y", ., ., . ), Add Factor( Blocking, 8, "Day" ),
Add Factor( Blocking, 2, "Time of Day" ),
Add Factor( Continuous, -1, 1, "X3", 0 ),
Add Factor( Continuous, -1, 1, "X4", 0 ), Set Random Seed( 353 ),
Add Term( {1, 0} ), Add Term( {3, 1} ), Add Term( {4, 1} ), Add Term( {1, 1} ),
Add Term( {2, 1} ), Add Alias Term( {3, 1}, {4, 1} ), Set Sample Size( 32 ),
Simulate Responses( 0 ), Save X Matrix( 0 )}
);
```

Learn it once, use it forever!

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##

So for 4 time intervals/day in Time of Day I need to turn the labels 5 6 7 8 and 9 10 11 12 and 13 14 15 16 to 1 2 3 4 ? And in the table the column Day must be ordenened 1 to 4 and then in each day block ordening Time in Day 1 to 4 I got the final DOE?

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Re: Row-column experiment with two crossed blocking factors

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Re: Row-column experiment with two crossed blocking factors

The naming of the block levels will work either way. If you change the labels for time of day to mean first, second. and so on, then you must indicate that the level is nested in the day factor for the time of day effect in the model.

The ordering of the block levels is a convenience to you. It is not necessary for the analysis.

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Re: Row-column experiment with two crossed blocking factors

**within** day. So the numbering is "in question". When you use the coding 1-4, 1-4 for the time intervals (for 2 days), the software recognizes the 1 for time interval for day 1 to be "identical" to the time interval 1 for day 2. While the time interval is similar, it can not be identical. I would call it systematic. I could argue (both ways) the systematic pattern within day is close enough to the same to investigate the interaction or I could argue that it is definitely not the same, hence it is nested. I think it extremely important that you have hypotheses to support the time intervals within day are similar enough to justify the crossed nature of the effects.

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Re: Row-column experiment with two crossed blocking factors

Adding to @statman, the Day and Time of Day effects should probably be defined as random effects in the model.

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Thanks for reply. Indeed the levels of Time of day are nested in the day blocking factor; it is an experiment where several effects (quite a umber of runs are required) have to be tested during a number of days because only 4 runs/day are possible, however also during one day temperature and weather conditions can change so each day block needs to be split into 4 different time intervals (in each time interval conditions are assumed to be +/- stable) --> how do I indicate this nesting in custom design?

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Re: Row-column experiment with two crossed blocking factors

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Re: Row-column experiment with two crossed blocking factors

You cannot indicate nesting or random effects in Custom Design. You modify the model in the Fit Model launch dialog. You can save the updated model to the data table for future use.

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Re: Row-column experiment with two crossed blocking factors

The key to proper analysis is the model you create. The numbering in @markbailey's post would work for nesting (sequential, non-repeating).

The concept of a block is "theoretically" to hold the noise variables constant within the block thereby increasing the precision of detecting factor effects and *allow* (or manipulate) those noise variables so they change between blocks, thereby increasing the inference space while not negatively effecting the precision. You are in a situation, where some of the noise variables are changing within the block. This "theoretically" will increase the error within the block reducing the precision of detecting factor effects. Can you choose your blocks differently? Is the within day variation in ambient conditions greater than the between day? Some other options:

1. Measure ambient conditions and treat those measurements as a covariate (e.g., dew point)

2. Use a center point treatment (current conditions?) or perhaps an identical treatment combination to replicate over the course of the experiment. Analyze this and use the mean square of this replicated treatment as a basis for statistical tests (error estimate).

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This covariate approach is interesting! Over the entire field expeiment identical concitons are nearly imossible so center point replication is no option also there may be lot of vaiation between the daily time intervals. Thanks for inputs I will now try to work out a DOE with seven fixed effects using Marc's nesting approach.

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Re: Row-column experiment with two crossed blocking factors