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Section 3.2: Experiments in the Real World. Equal Treatment for All in Experiments The experimenter must know exactly what treatments and responses he.

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Presentation on theme: "Section 3.2: Experiments in the Real World. Equal Treatment for All in Experiments The experimenter must know exactly what treatments and responses he."— Presentation transcript:

1 Section 3.2: Experiments in the Real World

2 Equal Treatment for All in Experiments The experimenter must know exactly what treatments and responses he wants information about. The experimenter must provide all materials needed for the treatments and to measure the responses. All subjects must be treated alike, except for the treatment assigned to them; any unequal treatment can cause …  BIAS!!!  It’s not an easy task to treat them alike.

3 Double-Blind Experiments Neither the subjects nor the people who work with them know which treatment each subject is receiving. Why is this so important???  If a subject knew they were receiving the placebo, the placebo effect would be weakened and bias in favor of the other treatment(s) would be increased.  If a subject knew they were receiving the treatment, they might expect results that may or may not occur.  Doctors’ expectations change with how they interact with patients and even the way they diagnose a patient’s condition if they know which treatment a subject has received.

4 Double-Blind Experiments Until the end of the study and the results are in, only the study’s statistician knows for sure who has the treatment and who has the placebo. The cartoon brings us back to non-sampling errors from Chapter 2…the knowledge of vocabulary is very important!!!

5 Problems that Happen During Experiments Sample surveys – non-response due to failure to contact or refusal to participate Experiments – refusal to participate, non-adherer to treatment, dropout  Refusal: Potential subjects may refuse to participate, which can cause undercoverage of certain groups in the subject population.  Non-adherers: Subjects participate, but don’t follow the experimental treatment as defined. They may add or omit other medications which may or may not be part of the experiment.  Dropouts: Subjects leave the experiment before its conclusion. If reason is not related to the treatment (they move away), no bias has occurred. If the reason for dropout is related to the treatment (reaction to treatment), bias can result.

6 What do you think??? What will Agent B be doing wrong? What will Agent Q be doing wrong? What will Agent K be doing wrong? B = treated differently Q = non-adherer K = dropout

7 Your Homework… Find print (magazine/newspaper) or online info regarding a clinical trial. Print or photocopy entire article and bring to class on Friday. Make sure it has information about the procedures of the experiment. Again, this is due in class on Friday. Tomorrow, we will be passing back papers and passing out the books which we have. Those which do not get a book will get a photocopy of Chapter 3. I have been told books will be here this week (cross your fingers). If you have borrowed a book, with permission or not, please bring it tomorrow so I can properly check it out. Quiz for 3.1 is on block day.

8 HW Turn In #5 #3.1A (state yes or no and give reason) #3.6A (state the response variable) #3.9B (state the first 5 rooms to the flat-rate group) #3.14 (state 1 lurking variable)

9 Section 3.2: Experiments in the Real World Day 2

10 Completely Randomized Experimental Design All subjects are randomly assigned to groups, and all groups are given different treatments. So far the examples have had only one explanatory variable (ex., drug vs. placebo). A completely randomized design can have any number of explanatory variables…

11 Example of Two Explanatory Variables In this example, there are two explanatory variables to describe the durability of fabric under repeated washings. The type of cleansing agent and the temperature of the water are both explanatory variables which are being tested. This produces 9 different treatments. A combination effect is called an interaction.

12 Matched Pair Designs Combines matching with randomization. It is an example of block designs. Compares just two treatments. Choose pairs of subjects as closely matched as possible. Assign one treatment to each subject by tossing a coin or reading odd and even digits from Table A. (every heads goes to group 1, every tails to group 2). Sometimes a matched pair is one person who tests two items, one after the other.

13 Block Design A block is a group of experimental subjects that have some commonality that is known before the experiment that could affect the response to the treatments (could be divided by gender, age range, etc.). In a block design, the random assignment of subjects to treatments is carried out separately within each block (like two, or more, randomized comparative experiments).

14 Example of a Block Design What type of sample design is a block design similar to?

15 In Your Groups In your groups, complete the following problem:  Most motor vehicles are equipped with catalytic converters to reduce harmful emissions. The ceramic used to make the converters must be baked to a certain hardness. The manufacturer must decide which of three temperatures (500°, 750°, and 1000°F) is best. The position of the converter in the oven (front, middle, or back) also affects the hardness. So there are two experimental factors: temperature and placement.  A. List the treatments in this experiment if all combinations of levels of the two factors are used.  B. Design a completely randomized experiment with five units in each group.  C. Using Table A, beginning at line 101, do the randomization for your experiment.

16 Homework Assignment #11  Page 159 #3.24, 3.25  Pages , #3.27, 3.29, 3.30  Pages , #3.32, 3.33, 3.34  Remember to bring your clinical study article to class on Friday.


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