Part I
1. How many independent variables are in a 4X6 factorial design? How many conditions are in this design?
There are 4 and 6 independent variables, and 24 conditions for this design.
2. What is the difference between a cell mean and the means used to interpret a main effect?
The main effect is used to interpret the differences in means over levels of one factor collapsed over levels of the other factor (Jackson, 2012). However, the cell mean is used to interpret is used with models that include three-way interactions. In addition, a cell means is used with mixed procedures (Jackson, 2012).
3. What is the difference between a complete factorial design and an incomplete factorial design?
The complete factorial design consists of all combinations of all factor-levels of each factor; and it can estimate all factors and their interactions (Collins, Dziak, & Li, 2009; Jackson, 2012). In addition, the fixed-level designs may be calculated (Collins, Dziak, & Li, 2009). For example, a two-level factor, a three-level factor, and a four-level factor has 2 x 3 x 4 = 24 runs.
The incomplete factorial design some of the cells are intentionally left empty, where participants will not be assigned to those combinations of factors. It is most likely to be used in a controlled group (Trochim, 2000; Jackson, 2012). Therefore, the research can evaluate relative treatment comparisons within a single study and be able to determine the effect of different treatment combinations (Trochim, 2000; Jackson, 2012).
4. Explain the difference between a two-way ANOVA and a three-way ANOVA?
A one-way ANOVA is used when the research wants to evaluate the differences between variables (Kirk, 1995; Jackson, 2012). For example, a study may evaluate the dif...
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...her factor (Trochim & Donnelly, 2008).
How does a covariate reduce noise?
An ANCOVA design is a noise-reducing experimental design can adjusts posttest scores for variability on the covariate pretest. Covariates are the variables you adjust for, where the effect is going to be removed. Any continuous variable can be used as the covariate; however, the pretest is usually best (Trochim & Donnelly, 2008).
Describe and explain three trade-offs present in experiments.
Schank and Koehnle (2009) argued that the three trade-offs present in experiments are the inevitable in any decisions including blocking or to standardize conditions in experiments. The interpretation of multiple tests of a hypothesis is clarified. Experiments with large samples raise the possibility of small, but statistically significant, biases even after randomization of treatments (Wiley, 2009).
1995). Kolotkin et al. (1995) built their experiment on the belief that, “monitoring factors suc...
The recommended design for this type of study is a non-equivalent control group post-test only design.
Going into details of the article, I realized that the necessary information needed to evaluate the experimental procedures were not included. However, when conducting an experiment, the independent and dependent variable are to be studied before giving a final conclusion.
Wang, X., Mears, D. P., Spohn, C., & Dario, L. (2013). Assessing the Differential Effects of
...nclude Mono-Operation bias, according to Trochim & Donnelly (2008), which is a threat to construct validity that happens when there is a problem with your operationalization of your independent variable versus the construct on which it was based. Another design threat is that of the Mono-Method bias and this threat to construct validity refers to the use of only one method of measurement i.e. (you can’t provide proof that you are measuring what you say you are measuring) (Trochim & Donnelly, 2008). In addition, and according to Trochim & Donnelly (2008), a threat to construct validity is that of Interaction of Different Treatments, which means that experiences outside of those being controlled by your experiment effect the outcome of the study. An additional threat to construct validity that is related to design is Interaction of Testing and Treatment, which is
Psychologist Lewis R. Goldberg reviewed the model and came up with the theory that the five factors are terms that over a long period of time, the human race has collectively narrowed down and use universally to describe an individuals personality. It gives individuals a sense of... ... middle of paper ... ...to psychology and outside of psychology is also a convincing argument for the support of the model. Bibliography DAVEY. G. (2004).
In conclusion, the title and context of the article are clear, and appropriately match the hypothesis of the authors. There is consistency between the objective of the experiment and its relationship to science. This writer found some issues in the overall presentation of information, in that the text lacks smooth transition, and was difficult to read and follow.
...s strength in the experiment rather than a limitation which future studies should also monitor.
In order to have a successful, reliable experiment you need sufficient data and evidence, reliable research, variables to test and a follow – up experiment. There are several types of variables you need to do an experiment. An independent variable is the manipulated experimental factor that is changed to see what the effects are. A dependent variable is the outcome. This factor can change in an experiment in reaction to the changes in the independent variable. An experimental group is the group of participants that are exposed to the change that the independent variable represents. The control group is participants who are treated in the same way as the experimental group except for the manipulated factor which is the independent variable (King 24). Proper data, evidence and research is also needed so the experiment turns out correctly and you know what you are testing. A follow – up experiment is not required, however it helps the validity of the conclusion of the experiment. Validity is “the soundness of the conclusions that a researcher draws from an experiment” (King 25). Conducting a follow – up experiment will help researchers and people alike see if the experiment worked properly, continues to help people and see how participants are doing after the experiment is over.
The implication of the level of measurement would be analyses require a minimum level of measurements and some variables can be treated as multiple level of treatment."
This is a within subjects repeated measures design where each animal will receive each level of the independent variable and will serve as its own control. The data will be analyzed with a one-way within-subjects anova.
In simplest terms, an experiment that uses only between-subjects factors is said to use a between-subjects design, and an experiment that uses only within-subjects factors is called a within-subjects design. The fundamental hallmark of a between-subjects design is that each participant is assigned to one and only one level of each factor. For instance, participants might be randomly assigned to either receive negative feedback or positive feedback. Feedback is the independent variable, and it has two levels: positive or negative. It is a between-subjects design because each participant only receives one type of feedback. There are two (2) independent groups of participants in the study: one group receives positive feedback and the other group receives negative feedback (Charness, Gneezy, & Kuhn, 2012). In a between-subjects design, the typical approach to statistical analysis is to compare the means of the different levels of the between-subjects factors. Using the above explanation, an experimenter might measure each participant’s self esteem, for example, after he/she has received feedback. The mean self-esteem score for the positive feedback group would than be compared to the mean self-esteem score for the negative feedback group (Thompson & Campbell, 2004). The experimenter’s goal, in this example, would be to explain as much of the variance as possible between the two means: positive and negative. The variance that can be explained is the variance due to being in the positive versus the negative feedback condition. The variance can be explained because you have an independent variable; in this experiment, it would be the feedback condition. However, the experimenter could not explain why one participant in the...
five factor theory is a fairly recent proposal and has its basis in earlier work,
Randomized Controlled Trials can be used to in several types of evaluations, including new therapies (i.e. Cognitive behavioral therapy versus emotionally focused therapy when treating couples), community interventions, and diagnostic techniques (O'Brien, 2013). The RCT study design randomly assigns participants into an experimental group or a control group. As the study is conducted, the only expected difference between the control and experimental groups is the outcome variable being studied (O'Brien, 2013).
Researchers work hard to eliminate bias from outcomes through approaches that diminish subjectivity and modification from unknown sources. Randomization, use of well-matched controls, and blinding of analysts and researchers are some ways to try to a...