Add pseudoreplication, closes #32

Author: mine-cetinkaya-rundel

02-data-design.Rmd

@@ -534,8 +534,7 @@ terms_chp_2 <- c(terms_chp_2, "experiment", "randomized experiment")
 
 ### Principles of experimental design
 
-1.  **Controlling.** Researchers assign treatments to cases, and they do their best to **control** any other differences in the groups[^data-design-6].\
-    For example, when patients take a drug in pill form, some patients take the pill with only a sip of water while others may have it with an entire glass of water. To control for the effect of water consumption, a doctor may instruct every patient to drink a 12 ounce glass of water with the pill.
+1.  **Controlling.** Researchers assign treatments to cases, and they do their best to **control** any other differences in the groups[^data-design-6]. For example, when patients take a drug in pill form, some patients take the pill with only a sip of water while others may have it with an entire glass of water. To control for the effect of water consumption, a doctor may instruct every patient to drink a 12 ounce glass of water with the pill.
 
 [^data-design-6]: This is a different concept than a *control group*, which we discuss in the second principle and in Section \@ref(reducing-bias-human-experiments).
 
@@ -549,10 +548,17 @@ terms_chp_2 <- c(terms_chp_2, "control")
 
 3.  **Replication.** The more cases researchers observe, the more accurately they can estimate the effect of the explanatory variable on the response.
     In a single study, we **replicate** by collecting a sufficiently large sample.
-    Alternatively, a group of scientists may replicate an entire study to verify an earlier finding.
+    What is considered sufficiently large varies from experiment to experiment, but at a minimum we want to have multiple subjects (experimental units) per treatment group.
+    Another way of achieving replication is replicating an entire study to verify an earlier finding.
+    The term **replication crisis** refers to the ongoing methodological crisis in which past findings from scientific studies in several disciplines have failed to be replicated.
+    **Pseudoreplication** occurs when individual observations under different treatments are heavily dependent on each other.
+    For example, suppose you have 50 subjects in an experiment where you're taking blood pressure measurements at 10 time points throughout the course of the study.
+    By the end, you will have 50 $\times$ 10 = 500 measurements.
+    Reporting that you have 500 experimental units would be considered pseudoreplication as the blood pressure measurements of a given individual are not independent of each other.
+    Pseudoreplication often happens when the wrong entity is replicated and reported sample sizes are exaggerated.
 
 ```{r include=FALSE}
-terms_chp_2 <- c(terms_chp_2, "replicate")
+terms_chp_2 <- c(terms_chp_2, "replicatation", "pseudoreplication", "replication crisis")
 ```
 
 4.  **Blocking.** Researchers sometimes know or suspect that variables, other than the treatment, influence the response. Under these circumstances, they may first group individuals based on this variable into **blocks** and then randomize cases within each block to the treatment groups. This strategy is often referred to as **blocking**. For instance, if we are looking at the effect of a drug on heart attacks, we might first split patients in the study into low-risk and high-risk blocks, then randomly assign half the patients from each block to the control group and the other half to the treatment group, as shown in Figure \@ref(fig:blocking). This strategy ensures that each treatment group has the same number of low-risk patients and also the same number of high-risk patients.