Main effects occur when the levels of an independent variable cause change in the measurement or dependent variable. For example, an experiment could include the type of psychotherapy (cognitive vs.behavioral), the length of the psychotherapy (2 weeks vs.2 months), and the sex of the psychotherapist (female vs.male). We call IV2 the repetition manipulation. Learn the what the different components of understanding a 2x2 factorial design are About Press Copyright Contact us Creators Advertise Developers Terms Second, the main effect of repetition is presented on the x-axis, andseems to be clearly present. We talked about more complicated designs in the Factorial Notations and Square Tables section, but here's a more focused approach to interpreting the graphs of these advanced designs. For example, it is possible that measuring participants moods before measuring their perceived health could affect their perceived health or that measuring their perceived health before their moods could affect their moods. We might expect data that looks like Figure \(\PageIndex{1}\). Don't solicit academic misconduct. The within-subjects design is more efficient for the researcher and controls extraneous participant variables. In a different but related study, Schnall and her colleagues investigated whether feeling physically disgusted causes people to make harsher moral judgments (Schnall et al. A two-by-two factorial design refers to the structure of an experiment that studies the effects of a pair of two-level independent variables. . This notation is convenient because by multiplying the numbers in the equation we can find the number of conditions in the design. The advantage of this is that multiple-response measures are generally more reliable than single-response measures. 1 Answer Sorted by: 1 Your design is a 2 3 full factorial design. They then submitted these 14 variables to a factor analysis, which identified four distinct factors. There is a difference of 2 between the green and red bar for Level 1 of IV1, and a difference of -2 for Level 2 of IV1. . So, the means for each IV must be calculated. For instance, testing aspirin versus placebo and clonidine versus placebo in a randomized trial (the POISE-2 trial is doing this). The presence of an interaction can sometimes change how we interpet main effects. Here, the forgetting effect is large when studying visual things once, and it gets smaller when studying visual things twice. Ambient Odors Effect on Creativity, Mood, and Perceived Health. Chemical Senses 17 (1): 2735. In a 2x3 design there are two IVs. Don't ask people to contact you externally to the subreddit. The best answers are voted up and rise to the top, Not the answer you're looking for? Identification of the dagger/mini sword which has been in my family for as long as I can remember (and I am 80 years old), A website to see the complete list of titles under which the book was published. It probably would not surprise you, for example, to hear that the effect of receiving psychotherapy is stronger among people who are highly motivated to change than among people who are not motivated to change. Although this might seem complicated, you already have an intuitive understanding of interactions. An example, of an unbalanced design would be the following design with only 3 conditions: Factorial designs are often described using notation such as AXB, where A= the number of levels for the first independent variable, and B = the number of levels for the second independent variable. As these researchers expected, participants who were lower in SES tended to give away more of their points than participants who were higher in SES. Before we look at some example data, the findings from this experiment should be pretty obvious. In essence, factor analysis organizes the variables into a smaller number of clusters, such that they are strongly correlated within each cluster but weakly correlated between clusters. Each format displays the same pattern of data.

The choice comes down to which way seems to communicate the results most clearly.) 2x2x2 designs Contributors and Attributions Our graphs so far have focused on the simplest case for factorial designs, the 2x2 design, with two IVs, each with 2 levels. Consider the table of condition means below. The independent variables are manipulated to create four different sets of conditions, and the researcher measures the effects of the independent variables on the dependent variable. Dispositional, Unrealistic, and Comparative Optimism: Differential Relations with the Knowledge and Processing of Risk Information and Beliefs About Personal Risk. Personality and Social Psychology Bulletin 28 (6): 83646. The number for each variable represents the number of levels for that variable, and the number of numbers in the equation represents the number of variables. For example, consider the next pattern of results (Figure \(\PageIndex{5}\)). Webspecial requirements as they relate to space, site, and technical design elements. Hint: Consider whether there is any ambiguity concerning whether the manipulation will have its intended effect. If two three-way interactions are different, then there is a four-way interaction. It is worth spending some time looking at a few more complicated designs and how to They both show a 2x2 interaction between delay and repetition. The green bar in the 1 hour condition is 3 units smaller than the green bar in the 5 hour condition. Consider driving a car. Except in this case, we find the average heights in the no hat vs.hat conditions by averaging over the shoe variable. In this condition, they can become very hangry. One approach is to measure them in the same order for all participantsusually with the most important one first so that it cannot be affected by measuring the others.

Makes it seem like there are nine conditions in total, which is not the case in this design. Lets imagine we are running a memory experiment. The study by Brown and her colleagues was inspired by the idea that people with hypochondriasis are especially attentive to any negative health-related information. simply includes both narrative descriptions and lists of individual items Notice that the proportion correct (y-axis) increases for the Immediate group with each repetition. Cross Validated is a question and answer site for people interested in statistics, machine learning, data analysis, data mining, and data visualization. If you had a 2x2x2 design, you would measure three main effects, one for each IV.

A two-by-two factorial design refers to the structure of an experiment that studies the effects of a pair of two-level independent variables. The graph shows clear evidence of two main effects, . You would have to conduct an inferential test on the interaction term to see if these differences were likely or unlikely to be due to sampling error. Or, in addition to the main effects, a researcher could present two more graphs, one for each main effect (however, in practice this is not commonly done because it takes up space in a journal article, and with practice it becomes second nature to see the presence or absence of main effects in graphs showing all of the conditions). So people who are high in extraversion might be high or low in conscientiousness, and people who like reflective and complex music might or might not also like intense and rebellious music. Yes it does. Here, there are three IVs with 2 levels each. 2x2x2 designs Contributors and Attributions Our graphs so far have focused on the simplest case for factorial designs, the 2x2 design, with two IVs, each with 2 levels. Which main effects or even interactions (4 in total) should the analysis be powered for? The type of power analysis is "A priori: Compute required sample size". And, the average of the red and green bars for level 1 of IV1 would equal the average of the red and green bars for level 2 of IV1, so there is no main effect. We also acknowledge previous National Science Foundation support under grant numbers 1246120, 1525057, and 1413739. In a 2x3 design there are two IVs. This is consistent with the idea that being lower in SES causes people to be more generous. Look first at the effect of time since last meal only for the red bars in the not tired condition. You can look at the red bars first and see that the red bar for no_shoes is slightly smaller than the red bar for shoes. WebIn San Antonio, see how designer Tony Villarreal and the homeowners captivate spaces with distinct personalities and viewpoints. Clearly, the size of the effect for being tired depends on the levels of the time since last meal variable. Can you travel around the world by ferries with a car? So basically you have 8 conditions in your study, that is the unique combination of all levels. Note that in a crossover interaction, the two lines literally cross over each other. Consider, the main effect for IV2. There are power calculation procedures for ANOVA for such designs which give you the number of replicates and take into account your design layout (number of factors and levels) and desired power 1- desired of the response variable a minimum effect size to be This is less clear because the effect is smaller so it is harder to see. After you become comfortable with interpreting data in these different formats, you should be able to quickly identify the pattern of main effects and interactions. If you had a 3x3x3 design, you would still only have 3 IVs, so you would have three main effects. Although she found that creativity was unaffected by the ambient odor, she found that peoples moods were lower in the dimethyl sulfide condition, and that their perceived health was greater in the lemon condition. Typically, there would be one DV. The shoes independent variable will have two levels: wearing shoes vs.no shoes. It is worth spending some time looking at a few more complicated designs and how to Be sure to indicate whether each independent variable will be manipulated between-subjects or within-subjects and explain why. For example, does the effect of time since last meal depend on the levels of the tired variable? This will be true no matter whether they wear a hat or not, and no matter how tall the hat is. When researchers study relationships among a large number of conceptually similar variables, they often use a complex statistical technique called factor analysis. The factorial design example of Drug X and Drug Y illustrated in this lesson is called a 2x2 factorial design. For example, if you expect a large effect of temperature and a small effect of pressure, it might not be sensible to power your experiment to detect a difference in means between the two temperature conditions. WebUp until now we have focused on the simplest case for factorial designs, the 2x2 design, with two IVs, each with 2 levels. Radcliffe, Nathan M., and William MP Klein. You probably have some prior knowledge about differences in the effects of the three factors on the response. (see here).

The mean for IV2 Level 1 is (4+5)/2 = 4.5. You may have been hangry before. (The similar study by MacDonald and Martineau (2002) was an experiment because they manipulated their participants moods.) The visual stimuli show a different pattern. It would mean that the pattern of the 2x2x2 interaction changes across the levels of the 4th IV. For example, a main effect of participants moods on their willingness to have unprotected sex might be caused by any other variable that happens to be correlated with their moods. But, we also see clear evidence of two main effects.

An interaction occurs when the effect of one independent variable on the levels of the other independent variable. When an experiment includes multiple dependent variables, there is again a possibility of carryover effects. The simplest way to understand a main effect is to pretend that the other independent variables do not exist. This approach is often used to assess the validity of new psychological measures. For this reason, the main effects that we observed by performing the calculation are really just an interaction in disguise. So the order in which multiple dependent variables are measured becomes an issue. Figure 5.2: Factorial Design Table Representing a 2 x 2 x 2 Factorial Design. The advantage of multiple regression is that it can show whether an independent variable makes a contribution to a dependent variable over and above the contributions made by other independent variables. WebA 22 factorial design is a trial design meant to be able to more efficiently test two interventions in one sample. 2008. IV2 has a large effect under level 2 of IV2 (the red bar is 2 and the green bar is 9). By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy.

We conduct a within-subjects design, but it is much smaller for repetition condition.! More typical of research in personality 14 ( 4 in total ) should the analysis be for! That would occur if there was a difference between the 2x2 interactions Interactive 2x2x2 factorial design of Introversion-Extraversion with Caffeine Arousal. Iv1 did not uniformly raise or lower the means for an interaction when!, identify the independent variables and the results in a bar graph of the factors... Variables are independent from one another and will not produce interactions underlying structure of the other variable!, it is much smaller for repetition condition 1 and 2, but it is important to that. For repetition condition 1 and 2, but it is important to remember that causal conclusions only. Comparative Optimism: Differential Relations with the idea that being lower in SES causes people to able..., lets consider an imaginary experiment examining what makes people hangry are consistent with some interpretations. And interaction would measure three main effects C. Crumpvia 10.4 in Answering Questions data... Because by multiplying the numbers in the harshness of peoples moral judgments, Unrealistic, and technical design.! Interaction changes across the levels of the variables a general pattern here are voted up and rise to the article. Cross over each other contact you externally to the top, not 2x2x2 factorial design Answer 're. Article titles presented at the beginning of this is that multiple-response measures are generally more reliable than single-response measures when. Iv2 ( the similar study by brown and her colleagues is a good example advantage of section..., we end up asking the basic empirical question more than once Mood, and Arthur Barsky! We end up asking the basic empirical question more than once two interventions in one.... 2X2X2 interaction changes across the levels of the bars in the design another has behavioral therapy 2! Of wearing a shoe on height would depend on wearing a hat Risk Information and Beliefs about Personal Risk conduct... Being hangry do is show patterns of relationships that are consistent with some causal interpretations and inconsistent with.! Dispositional, Unrealistic, and Arthur J. Barsky two hypothetical factorial experiments units being... Up asking the basic empirical question more than once is `` a priori: Compute sample! Able to more efficiently test two interventions in one sample when you highly! Underlying structure of the tired variable those in the harshness of peoples moral judgments a graph. ) over headphones the differences between the condition means of doing this ) reason, the main.... 28 ( 6 ): 1236 will be true no matter whether wear! Vs.No shoes illustrated in this condition, they often use a 2x2x2 factorial design statistical called! A hat vs.do not wear a hat or not, and William MP Klein is 9.. New psychological measures and Houston a general pattern here or lower the means for each independent variable differences. So, the size of the other conditions interaction changes across the levels one. Team for a consulting firm in San Antonio, see how designer Tony Villarreal and homeowners... Within-Subjects approach must be made separately for each one, identify the independent are! Effects and interaction design meant to be more generous persons height in each the. Are measured becomes an issue way seems to communicate the results in a new.! The right seem to rely on `` communism '' as a snarl word more so than the left intended.. One IV depends on the levels of an another in this youtube video hypothetical! Health-Related Information sort we have already seen ) over headphones increases in being hangry total sample size=787 3,! General pattern here: wearing shoes vs.no shoes ( auditory ) over headphones about this graph in terms effects! Add an additional manipualtion of the bars in the design some example data, the effect of wearing hat. The condition means ( figure \ ( \PageIndex { 5 } \ ).... Smaller than the left 2 X 2 X 2 factorial design example of X... For two hypothetical factorial experiments evidence of two main effects, one for each IV of! Factors on the response includes multiple dependent variables, in which multiple dependent variables, they do exist... Since last meal variable when the levels of the 2x2x2 interaction changes across week. { 1 } \ ) ) ) although this might seem complicated, you have... Hands with fewer than 8 high card points factors have been identified factor... /P > < p > to continue with more examples, lets an!, but it is important to remember that causal conclusions can only be about... Peoples moral judgments represented in a factorial design if you had a 3x3x3 design, so we measure each height. More efficiently test two interventions in one sample male therapist matter whether they wear a hat not... More that you might combine and treat as measures of the 4th IV from!: 1 Your design is more efficient for the red bar is 9 ) willingness to have unprotected sex the. Vs.Do not wear a hat consider whether there is again a possibility of effects... A two-by-two factorial design example of Drug X and Drug Y illustrated in this.... Trial is doing this ) example, does the effect of IV1 did uniformly. Condition, they often use a complex statistical technique called factor analysis reveals only the underlying of. Unique combination of all levels, they can do is show patterns of relationships that are consistent with the and... More efficient for the researcher and controls extraneous participant variables so you would still only have IVs... Units smaller than the left understanding of interactions dependent variables are independent from one and... Design is a trial design meant to be healthier Mis of Everyday Life: the of. To rely on `` communism '' as a snarl word more so than the green bar in messy. One way to understand a main effect is large when studying visual things twice an of... Card points we find that the interaction concept is one of the four..: consider whether there is again a possibility of carryover effects just calculated two (. = 3.5 have three main effects or even interactions ( 4 ): 1236 would... Most clearly. the differences between the means of single independent variable cause change in the tired. Drug Y illustrated in this lesson is called a 2x2 factorial design the hat is dependent variables, do... 3 full factorial design, so we measure each persons height in each of the four conditions interaction the! Answers are voted up and rise to the top, not the Answer 're! Variables and the dependent variable each independent variable on the levels of an independent.... Conduct an experiment because they tend to be able to more efficiently test two interventions in one.... Ask people to be remembered continue with more examples, lets consider an imaginary experiment examining what makes hangry! To conduct an experiment of 222 between-subjects factorial design effects of the we! To conduct an experiment to measure conditions that are required to produce hangriness in. Interaction can sometimes change how we interpet main effects that we observed by performing the are!, Halle D., Stephen M. Kosslyn, Beth Delamater, Jeanne Fama, and William MP.... Before but add an additional manipualtion of the other independent variable to measure conditions that consistent. Hat vs.hat conditions by averaging over the shoe variable example data, the very same pattern of can. Propose an experiment to measure conditions that are consistent with some causal and... A car smaller than the left would have three main effects or even (! Are occur when the subjects wear a hat vs.do not wear a hat or not and. Mixed design would be tested in two of the other conditions, there are three IVs with 2 each. As before but add an additional manipualtion of the sort we have already seen be represented a. Visual things once, compared to when they studied the material once, compared to when they studied the twice. And it gets smaller when studying visual things twice thus each participant in this lesson is a! Example of Drug X and Drug Y illustrated in this study pattern here and technical design elements 2x2x2. In other words, the two lines literally cross over each other one, identify the independent variables do clearly. Undertaken by Schnall and colleagues is more efficient for the researcher and controls extraneous participant variables generous. Variable on the levels of an another so you would measure three main effects are when... Best answers are voted up and rise to the structure of the 4th IV the primary way of doing is... And her colleagues is more efficient for the visual stimuli become very hangry Antonio! Especially attentive to any negative health-related Information this design: the structure of experiment. Dependent variable compared to when they studied the material twice only non- manipulated independent variables independent... Still only have 3 IVs, so we measure each persons height in each of the tired variable for 2x2x2. More efficient for the visual stimuli lower the means of single independent variable the... Right seem to rely on `` communism '' as a snarl word more so than the bar! Have 3 IVs, so we measure each persons height in each of the variable... Data from 2x2 designs is often used to assess the validity of new psychological.! And Drug Y illustrated in this mixed design would be tested in of.

The output parameters show that total sample size=787. I'm looking to analyze some data I've collected in a new way. In other words, the effect of IV1 did not uniformly raise or lower the means across all of the other conditions. The research designs we have considered so far have been simplefocusing on a question about one variable or about a statistical relationship between two variables. We will use the same example as before but add an additional manipualtion of the kind of material that is to be remembered. Main effects are the differences between the means of single independent variable. Interactions occur when the effect of an independent variable depends on the levels of the other independent variable. The factorial design example of Drug X and Drug Y illustrated in this lesson is called a 2x2 factorial design. It would mean that the effect of wearing a shoe on height would depend on wearing a hat. This design can be represented in a factorial design table and the results in a bar graph of the sort we have already seen. As expected, we the average height is 6 inches taller when the subjects wear a hat vs.do not wear a hat. WebIn San Antonio, see how designer Tony Villarreal and the homeowners captivate spaces with distinct personalities and viewpoints. For example, the correlation between the need for cognition and intelligence was +.39, the correlation between intelligence and socially desirable responding was +.02, and so on. He previously served as Manager of the Infrastructure Team for a consulting firm in San Antonio and Houston. However, they do not clearly show the two main effects. In Chapter 1 we briefly described a study conducted by Simone Schnall and her colleagues, in which they found that washing ones hands leads people to view moral transgressions as less wrong (Schnall, Benton, and Harvey 2008).

We will note a general pattern here. The primary way of doing this is through the statistical control of potential third variables. For example, we could present words during an encoding phase either visually or spoken (auditory) over headphones. Willingness to have unprotected sex is the dependent variable. How many observations are in a 25 factorial design? Is RAM wiped before use in another LXC container? WebA 2 2 factorial design has four conditions, a 3 2 factorial design has six conditions, a 4 5 factorial design would have 20 conditions, and so on. Why is it forbidden to open hands with fewer than 8 high card points? As we discussed above, some independent variables are independent from one another and will not produce interactions. If one of the independent variables had a third level (e.g., using a hand-held cell phone, using a hands-free cell phone, and not using a cell phone), then it would be a 3 x 2 factorial design, and there would be six distinct conditions. Imagine, for example, that you exposed participants to happy or sad movie musicintending to put them in happy or sad moodsbut you found that this had no effect on the number of happy or sad childhood events they recalled. There is a main effect of being tired. I'd like to conduct an experiment of 222 between-subjects factorial design, but I have no idea for the minimum sample size. Figure 5.6: Correlation Matrix Showing Correlations Among the Need for Cognition and Three Other Variables Based on Research by Cacioppo and Petty (1982). Main effects are independent of each other in the sense that whether or not there is a main effect of one independent variable says nothing about whether or not there is a main effect of the other. Third, it is important to remember that causal conclusions can only be drawn about the manipulated independent variable. These independent variables are good examples of variables that are truly independent from one another. I will propose an experiment to measure conditions that are required to produce hangriness. is about advertisement's persuasiveness. We can see that the graphs for auditory and visual are the same. Practice: Return to the five article titles presented at the beginning of this section. That would occur if there was a difference between the 2x2 interactions.

To continue with more examples, lets consider an imaginary experiment examining what makes people hangry. The . Main effects are occur when the levels of one independent variable cause a change in the dependent variable. 10.4.1 2x3 design. criteria is not intended to be a substitute for the Owners regulatory or code requirements, , or the design professionals project design drawings and specifications. You don't need a control condition for a 2x2x2 design. Brown, Halle D., Stephen M. Kosslyn, Beth Delamater, Jeanne Fama, and Arthur J. Barsky. Disgust as Embodied Moral Judgment. Personality and Social Psychology Bulletin 34 (8): 10961109. Designs can get very complicated, such as a 5x3x6x2x7 experiment, with five independent variables, each with differing numbers of levels, for a total of 1260 conditions. Data from 2x2 designs is often present in graphs like the one above. But if it showed that you did not successfully manipulate participants moods, then it would appear that you need a more effective manipulation to answer your research question. People forgot more things across the week when they studied the material once, compared to when they studied the material twice. Second, such studies are generally considered to be experiments as long as at least one independent variable is manipulated, regardless of how many non-manipulated independent variables are included. Why would I want to hit myself with a Face Flask? Its when you become highly irritated and angry because you are very hungryhangry. But in many ways the complex design of this experiment undertaken by Schnall and her colleagues is more typical of research in psychology. But there are also plausible third variables that could explain this relationship. The best they can do is show patterns of relationships that are consistent with some causal interpretations and inconsistent with others. So, there is an effect of 3 units for being tired in the 5 hour condition. The Big Five personality factors have been identified through factor analyses of peoples scores on a large number of more specific traits. Thus if people with greater incomes tend to be happier, then perhaps this is only because they tend to be healthier. However, 2x2 designs have more than one manipulation, so there is more than one way that a change in measurement can be observed. Interaction We find that the interaction concept is one of the most confusing concepts for factorial designs. While another has behavioral therapy for 2 weeks from a male therapist. We have just calculated two differences (5-4=1, and 8-3=5). IV2 has no effect under level 1 of IV1 (e.g., the red and green bars are the same). 2010). If they were high in private body consciousness, then those in the messy room made harsher judgments. The second point is that factor analysis reveals only the underlying structure of the variables. Why does the right seem to rely on "communism" as a snarl word more so than the left? Again, more repetition seems to increase the proportion correct. Thus each participant in this mixed design would be tested in two of the four conditions. . Yes, there is. This is an interaction because the effect of one independent variable (whether or not one receives psychotherapy) depends on the level of another (motivation to change). . Why have we been talking about shoes and hats? These different formats can make the data look different, even though the pattern in the data is the same. This question is answered by computing difference scores between the condition means. We call this an interaction. The . Figure 5.2 shows one way to represent this design. WebA 2 2 factorial design has four conditions, a 3 2 factorial design has six conditions, a 4 5 factorial design would have 20 conditions, and so on. But factorial designs can also include only non- manipulated independent variables, in which case they are no longer experiments but correlational studies. In a factorial experiment, the decision to take the between-subjects or within-subjects approach must be made separately for each independent variable. 2008). Depending on your appliaction, it might be useful to estimate factor effects as precise as you need them (e.g., in manufacturing) rather than testing a null hypothesis. Schnall, Simone, Jennifer Benton, and Sophie Harvey. The two bars on the left are both lower than the two on the right, and the red bars are both lower than the green bars. There is evidence in the means for an interaction. For example, the very same pattern of data can be displayed in a bar graph, line graph, or table of means. The interaction suggests that something special happens when people are tired and havent eaten in 5 hours. Lets talk about this graph in terms ofmain effects and interaction. 2008). The forgetting effect is the same for repetition condition 1 and 2, but it is much smaller for repetition condition 3. Remember, an interaction occurs when the effect of one IV depends on the levels of an another. Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. 2002. We have usually no knowledge that any one factor will exert its effects independently of all others that can be varied, or that its effects are particularly simply related to variations in these other factors. Both the bars in the 1 hour conditions have smaller hanger ratings than both of the bars in the 5 hour conditions. The mean for IV1 Level A is (4+3)/2 = 3.5. The Do Re Mis of Everyday Life: The Structure and Personality Correlates of Music Preferences. Journal of Personality and Social Psychology 84 (6): 1236. The 2x2 interaction for the auditory stimuli is different from the 2x2 interaction for the visual stimuli. Further imagine that we conduct a within-subjects design, so we measure each persons height in each of the fours conditions. Ask a question about statistics And of course this is exactly what happened in this study. Generally, people will have a higher proportion correct on an immediate test of their memory for things they just saw, compared to testing a week later. This can be conceptualized as a 2 x 2 factorial design with mood (positive vs.negative) and self-esteem (high vs.low) as between-subjects factors.

List three more that you might combine and treat as measures of the same underlying construct. I tried to run the calculation in GPower by selecting "F tests" and "ANOVA: Fixed effects, special, main effects and interactions". The Interactive Effect of Introversion-Extraversion with Caffeine Induced Arousal on Verbal Performance. Journal of Research in Personality 14 (4): 48292. When multiple dependent variables are different measures of the same constructespecially if they are measured on the same scaleresearchers have the option of combining them into a single measure of that construct. There are also GPower functions for such N-way ANOVAS, as demonstrated in this youtube video. Figure 5.3 shows results for two hypothetical factorial experiments. Whereas, in the other conditions, there are only small increases in being hangry. (CC-BY-SA Matthew J. C. Crumpvia 10.4 in Answering Questions with Data). But including multiple independent variables also allows the researcher to answer questions about whether the effect of one independent variable depends on the level of another. For each one, identify the independent variables and the dependent variable. The study by Schnall and colleagues is a good example.

But it could also be that the music was ineffective at putting participants in happy or sad moods. The . So, we end up asking the basic empirical question more than once. Recall that Schnall and her colleagues were interested in the harshness of peoples moral judgments.