In an independent groups design, what is the key feature and what is its main disadvantage?
A: Each participant appears in all conditions; disadvantage is order effects
B: Different participants are assigned to each condition; disadvantage is that participant variables may differ between groups
C: Participants are paired on key characteristics; disadvantage is the difficulty of finding matched pairs
D: Participants self-select which condition they join; disadvantage is demand characteristics
Correct: Different participants are assigned to each condition; disadvantage is that participant variables may differ between groups
In an independent groups (between-subjects) design, different participants are used in each condition — one group receives the experimental condition, another the control. The main advantage is that there are no order effects (participants only experience one condition, so practice or fatigue effects cannot transfer). The main disadvantage is participant variability: the two groups may differ in relevant ways (age, ability, personality) even before the experiment begins, meaning observed differences in the DV might reflect pre-existing group differences rather than the IV's effect. This is typically addressed by random allocation to conditions, which distributes individual differences randomly across groups rather than allowing them to cluster systematically.
What is a repeated measures design, and what threat does it introduce that an independent groups design avoids?
A: Each participant experiences all conditions; it introduces order effects (practice, fatigue, boredom)
B: Participants are tested repeatedly until they reach a criterion; it risks selection bias
C: Different groups are measured at repeated time points; it risks attrition bias
D: Each participant is matched to another; it risks demand characteristics
Correct: Each participant experiences all conditions; it introduces order effects (practice, fatigue, boredom)
In a repeated measures (within-subjects) design, the same participants complete all conditions. The major advantage is that participant variables are controlled — any differences between conditions cannot be due to pre-existing participant differences, since every participant serves as their own control. The main disadvantage is order effects: performance in a later condition may be affected by experience from an earlier one. These include practice effects (improvement due to familiarity with the task), fatigue effects (decline due to tiredness), and boredom effects. Demand characteristics may also be heightened, as participants who complete multiple conditions may more easily guess the study's purpose and alter their behaviour accordingly.
A researcher uses counterbalancing in a repeated measures experiment. What does this involve and what problem does it address?
A: Assigning equal numbers to each condition to control for participant variability
B: Systematically varying the order in which participants complete conditions so that order effects are distributed evenly rather than always benefiting one condition
C: Testing participants in pairs so that each has a matched control partner
D: Keeping the researcher blind to which condition each participant is in
Correct: Systematically varying the order in which participants complete conditions so that order effects are distributed evenly rather than always benefiting one condition
Counterbalancing is the standard solution to order effects in repeated measures designs. Rather than all participants completing conditions in the same order (A then B), half complete A then B and half complete B then A (ABBA counterbalancing, or Latin square designs for more conditions). If practice effects exist, they will improve performance in whichever condition comes second — and since "second" is sometimes A and sometimes B across participants, the benefit distributes evenly across conditions rather than systematically favouring one. Note that counterbalancing does not eliminate order effects — it balances them across conditions. It also requires twice as many participants as a simple ordering, and assumes that AB and BA order effects are symmetrical.
What is a matched pairs design and what is it trying to achieve?
A: Pairing each participant with a researcher to reduce experimenter bias
B: A hybrid design that combines the participant-variable control of repeated measures with the absence of order effects in independent groups, by pairing participants on key characteristics before assigning one to each condition
C: Randomly assigning matched numbers of male and female participants to each condition
D: Testing pairs of identical twins to eliminate all genetic variability
Correct: A hybrid design that combines the participant-variable control of repeated measures with the absence of order effects in independent groups, by pairing participants on key characteristics before assigning one to each condition
A matched pairs design attempts to get the best of both worlds. Participants are paired based on variables likely to affect the DV (e.g. IQ, age, baseline memory score), and one member of each pair is assigned to each condition. This reduces between-group variability compared to pure independent groups (reducing the impact of participant variability) while avoiding order effects (since each person only completes one condition, unlike repeated measures). The main disadvantage is the practical difficulty of finding well-matched pairs, especially on multiple variables simultaneously. It is also less powerful than repeated measures (where the same person appears in both conditions), because the pairs are never perfectly equivalent.
What distinguishes a laboratory experiment from a field experiment?
A: Laboratory experiments use only quantitative data; field experiments use qualitative data
B: Laboratory experiments take place in a controlled, artificial setting where the researcher manipulates the IV; field experiments take place in the participant's natural environment with the IV still manipulated by the researcher
C: Laboratory experiments use random sampling; field experiments use opportunity sampling
D: Laboratory experiments measure behaviour; field experiments measure self-reported attitudes
Correct: Laboratory experiments take place in a controlled, artificial setting where the researcher manipulates the IV; field experiments take place in the participant's natural environment with the IV still manipulated by the researcher
The defining difference is setting and control. In a laboratory experiment, the researcher brings participants into an artificial, controlled environment (a lab) and manipulates the IV — maximising control over extraneous variables and therefore internal validity. The trade-off is ecological validity: behaviour in an artificial setting may not reflect everyday behaviour. Field experiments take place in natural settings (schools, hospitals, streets, workplaces) with the IV still actively manipulated by the researcher — preserving ecological validity but sacrificing some control over extraneous variables. A natural experiment is a third type: the IV varies naturally (without researcher manipulation), such as comparing children's TV viewing before and after television was introduced to a community. Natural experiments have the highest ecological validity but the lowest control.
What are demand characteristics and why do they threaten validity?
A: The emotional demands placed on participants by stressful experimental tasks, which may cause them to drop out
B: Cues in the experimental situation that allow participants to guess the study's purpose and alter their behaviour accordingly, so that the DV reflects participants' responses to perceived expectations rather than the IV alone
C: The researcher's expectations about results, which may unconsciously influence how they treat participants in different conditions
D: The demand for ethical safeguards that must be met before any experiment can be approved
Correct: Cues in the experimental situation that allow participants to guess the study's purpose and alter their behaviour accordingly, so that the DV reflects participants' responses to perceived expectations rather than the IV alone
Demand characteristics are cues — in the task instructions, setting, materials, or the researcher's behaviour — that signal to participants what the study is about and what the "expected" or "desirable" response might be. Participants may then respond not to the IV itself but to their interpretation of what the researcher wants. This can produce two patterns: the screw-you effect (deliberate non-compliance with perceived expectations) or the please-you effect (trying to behave in the expected way). In either case, the DV no longer purely reflects the IV's effect, threatening internal validity. Single-blind designs (where participants do not know which condition they are in) and deception (used ethically) are common strategies to reduce demand characteristics.
In a double-blind experiment, who is kept unaware of which condition each participant is in?
A: Both the participants and the researcher collecting/scoring data
B: Both the participants and all members of the public who might read the study
C: Both the participants and the ethics committee reviewing the study
D: The participants only — the researcher must know to administer conditions correctly
Correct: Both the participants and the researcher collecting/scoring data
A double-blind procedure keeps both the participants and the researcher(s) interacting with or measuring participants unaware of condition allocation. This addresses two separate threats: demand characteristics (participants guessing and modifying their behaviour) and experimenter bias (researchers unconsciously treating participants differently across conditions or interpreting ambiguous data in line with their expectations). In drug trials, for example, neither the patient nor the administering clinician knows whether the patient is receiving the active drug or placebo — a separate team holds the allocation key. Single-blind means only participants are unaware; double-blind adds blinding of the data collectors and assessors as well.
What is a natural experiment, and what limits the conclusions that can be drawn from one?
A: An experiment conducted outdoors in natural settings, limiting conclusions because weather is an uncontrolled variable
B: A study in which the IV varies naturally or through circumstances beyond the researcher's control; conclusions about causation are limited because participants are not randomly allocated to conditions
C: An experiment using only naturalistic stimuli rather than artificial laboratory tasks; limited because stimuli may not generalise across cultures
D: A study with no ethical constraints because the researcher does not intervene; limited because it can only measure naturally occurring behaviours
Correct: A study in which the IV varies naturally or through circumstances beyond the researcher's control; conclusions about causation are limited because participants are not randomly allocated to conditions
In a natural experiment, the IV changes due to real-world events or circumstances — policy changes, natural disasters, the introduction of technology to a community — rather than researcher manipulation. Classic examples include Hodges and Tizard's study of children raised in institutions, and studies of children before and after television was introduced to communities. Because the researcher does not control who is exposed to each "condition," random allocation is impossible. Participants self-select or are determined by circumstance into conditions, meaning pre-existing differences between groups may explain any observed effect on the DV. Natural experiments therefore have high ecological validity but cannot establish causation with the same confidence as true experiments with random allocation and IV manipulation.
Experimental Design
In an independent groups design, what is the key feature and what is its main disadvantage?
About this quiz
Choosing how to assign participants to conditions is one of the most consequential decisions in research design. Independent groups, repeated measures, and matched pairs designs each carry their own strengths, weaknesses, and characteristic threats to validity — from order effects to participant variability to the practical demands of running a study.
This quiz covers the three core within- and between-participants designs, the experimental contexts they suit best, the controls researchers use to neutralise their weaknesses, and the distinction between laboratory, field, and natural experiments.