Research Methods Flashcards
(91 cards)
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Strengths of meta analysis
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Analysing results from a group of studies can allow more reliable conclusions to be drawn
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Meta analysis
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Combined the results of several studies that investigate a set of related research hypothesis (the same topic)
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Limitations of meta analysis
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Different studies analysed may be investigating the same topic but have used different methods or experimental designs>not comparable >not valid
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Content analysis
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Is the quantification of qualitative material. The data is quantified by using coding units. It is a form of indirect observation because you are not observing the people directly
E.g the numerical Analysis of speeches, advertisement or newspapers
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2 strengths of a content analysis
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Strengths:
- Has high mundane realism because they are based on direct observations of what people actually do; real communications which are current and relevant, such as recent newspapers
- when sources can be retained or accessed by others, findings can be replicated and so tested for reliability
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2 limitations of a content analysis
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- observer bias reduces the objectivity and validity of findings because different observers may interpret the meaning of the behavioural categories differently
- likely to be culture-biased because interpretation of verbal or written content will be affected by the language and culture of the observer and behavioural categories used
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Natural experiment
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The iv controls naturally but only records the effects of the iv on the dv
Method can be used when it is unethical to manipulate the iv
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Strengths of natural experiment
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-high mundane realism due to the naturally occurring environment therefore results relate to everyday behaviour and can be generalised to other settings
-no demand characteristics as participants are unw
Aware of experiment
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Limitations of natural experiments
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- more difficult to control extraneous variables therefore reducing internal validity
- difficult to replicate natural natural experiments because the conditions are never exactly the same
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Investigator effect
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Anything the investigator does or says which has an effect on the participants performance in the study
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Single blind
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The researcher makes sure participants don’t know the true aims of the study or which condition they are in
-prevents them from seeking cues and responding to them, cues are s type of extraneous variable. If participants did identify cues it would reduce validity
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Laboratory
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These are carried out in controlled conditions (usually a laboratory) and the researcher controls the IV and most EV
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Field
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These are carried out in a real world situation but the experimenter still manipulates the IV and EV’s as possible
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Natural
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These are carried out in the real world but the IV’s are naturally occurring/ going to happen anyway (researcher do not manipulate them)
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Longitudinal study
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when a study is conducted over a long period of time with regular intervals
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Laboratory strengths
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Allows the establishment of causality. Manipulating the independent variable to see if it causes an effect on the dependant variable.
Allows variable to be operationalised to increase validity and reliability of result
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Laboratory limitations
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- The high degree of control can make the experimental situation and unlike real life > the study will be low in external validity>making it difficult to generalise the results beyond the context of the study
- sometimes participants try to or can guess the purpose of the experiment from the task and this may alter their behaviour. Behaviour that is not genuine will reduce the validity of the results
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Field
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These are carried out in a real world situation but the experimenter still manipulates the IV and controls as many EV’s as possible
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Field experiment strengths
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- Less artificial than lab, so higher mundane realism
- In many cases participants are not aware of the study so there are less demand characteristics which will increase validity
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Field experiment limitations
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- extraneous variables are less easy to control so internal validity is reduced
- still a chance of demand characteristic
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Natural strengths
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- it has high mundane realism due to the naturally occurring environment >results relate to everyday behaviour and can be generalised to other
- there are no demand characteristics as participants are often unaware of the experiment>increases the internal validity of the findings
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Natural limitations
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- it is difficult to replicate natural experiments since the conditions are never exactly the same again> they are low in reliability
- it is more difficult to control extraneous variables therefore reducing internal validity
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Correlation analysis
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A correlational analysis involves measuring the relationship between two or more co-variables to see if a trend of pattern exists.
E.g looking at the relationship between the numbers of hours spent at a day and aggression levels
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3 types of correlations
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- positive correlation
- negative correlation
- zero correlation
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Positive correlation
This occurs when one co-variable increases as another co-variable increases
e.g ice cream sales increasing as the temperature increases
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Negatives correlation
This occurs when one co-variable increases while another decreases e.g raincoat sales decrease as the temperature
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Zero correlation
This occurs when there is no relationship between the factors
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Advantages of correlation
-Correlations show strength of relationships between co-variables. A correlation of 0.90 means a high positive correlation
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Weaknesses of correlation
- correlations are not conducted under controlled conditions and therefore do not show causality. Makes interpretations of results difficult
- may be other intervening variables that can explain Yh the co-variables being studied are linked
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Participant observation
This is where the observer becomes actively involved in the behaviour of the people being studied
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Non-participant
This involves researchers observing behaviour from a distance. They do not get actively involved in the behaviour being studied
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Overt
An observation is overt when the participants are aware that they are being observed
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Covert
An observation is covert when the participants are unaware that they are being observed
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Strength of observations
-they have high external validity as the observed behaviour takes place in the natural environment and results can be generalised to other settings
Participants are usually unaware of being observed and so there are few demand characteristics thus increasing the validity of the findings
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Limitations of observations (observer bias)
Observer bias- if observers know the purpose of the study, then they may be biased and see what they want to see which would reduce the reliability of the results. This could be overcome by having more than one observer and comparing their results to see if they have inter-rater reliability
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Self-report techniques
Structured interview (formal)
Definition
A fix set of questions is read to participants and the interviewer writes down responses. The questions are the same for all participants. Interviewers do not require much training
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Self report techniques
Structured interview (formal) strengths
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- can easily be replicated because the questions are standardised. A replicated study that finds similar results has improved reliability
- more easy to analyse than an unstructured interview because answers are more predictable
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Self report techniques
| Structured limitations
The interviewers expectations may influence the answers the interviewee gives reducing the validity of the results
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Self report techniques
| Unstructured (informal) interview
- These involve an informal discussion on a particular topic.
- Topic of the interview is predetermined whereas the direction of the interview is not.
- Friendly rapport between interviewer and respondent is important to gain the required level of detail and understanding
- interviewers need a lot of training
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Self report techniques
Unstructured (informal) interview
Strengths
- more detailed information can generally be obtained from each respondent than in a structured interview
- can access information that may not be revealed by predetermined questions
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Self report techniques
Unstructured (informal) interview
Limitations
- more likely for interviewer bias to occur than structured interviews because in an unstructured interview, the interviewer is developing new questions on the spot which might be less objective
- requires well-trained interviewers, which makes it more expensive to produce reliable interviews compared with structured
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Self report techniques
| Closed (fixed) and opened questions
- quick to carry out compared with other methods
- can be completed without researcher present and with postal surveys a large sample can be obtained
- questions are fixed questionnaires are easy to replicate the increasing the reliability of the findings
- Can collect qualitative and quantitative data for example you can get qualitative data= open questions and quantitative data =closed questions
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Case study definition
A research method that involves a detailed study of a single individual, institution or event it gathers information from a range of sources
-usually a longitudinal study
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Strengths of case study
In-depth data due to complex interaction many factors that may be overlooked using other methods
Used to investigate human behaviour that is rare or unethical to experiment with e.g. memory amnesia patients
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Limitations of case study
- external validity
- confidentiality
- internal validity
- difficult to generalise the findings to the rest of the population= low external validity
- confidentiality as an ethical issues raised because many cases identifiable due to their unique characteristics even when real names are not given
- asking the individual to recall information from the past means using information that is unreliable=low internal validity
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Llongitudinal study
When a study is conducted over a long period of time
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Strength of longitudinal study
| -
Allows the researcher to observe long term effects and make comparison between the same individual and different ages
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Limitation of longitudinals study
| -bias sample
-attrition is a problem. The people who drop out are more likely to have particular characteristics leaving a biased sample
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Null hypothesis
This is the hypothesis of no difference it predicts that the IV will not affect the DV
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Experimental designs
| Independent group definition
Different participants are tested in each condition
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Experimental designs
Independent group: strengths
-no order effects
-demand characteristics
- One advantage of this design is that there are no order effects as different participants do both conditions
- One condition so there is less chance that they will guess the purpose of the study and change their behaviour this means that there is less chance of demand characteristics
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Experimental designs
Independent group limitations
-participant variables
-Differences in the results between the two conditions may be due to participant variables (individual differences) rather than manipulations of the IV (can be minimised bye random sampling allocation of participants to each condition)
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Experimental designs
| Repeated measures definition
Each participant is tested in both conditions
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Experimental designs:
Repeated measures strengths
-participant variables
-saves time money and effort
- because the same people are measured in both conditions participant variables(the differences between individuals) are controlled
- as each participant produces two scores, twice as much data is produced compare to independent measures design so half as many participants to get the same amount of data saves money, time and effort
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Experimental designs
| Repeated measures limitations
- is order effects, means that part because participants are doing both conditions but in different order there can be an impact on the results -participants may perform worse in the second condition because they get bored or tired
- but they might perform better for you to practice, learning or increased confidence
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Experimental designs
| Matched pairs definition
Different participants are used in each condition but they are matched for specific characteristics
the characteristics must be relevant to what is being investigated
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Experimental designs
| Matched pairs strengths
A strength of matched pairs design is that different participants to both conditions there are no order affects and demand characteristics are reduced
Because the participants are more closely matched between conditions then independent groups design there is a reduced impact of participant variables
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Experimental designs
| Matched pairs limitations
It is impossible to match all valuables between participants and the one that is missed may affect the results
It is time-consuming and expensive to find suitably matched the participants
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Operationalised
This means the behaviour being observed should be broken down into a set of clear components
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The coding system/ behavioural checklist
Researchers need to develop behavioural categories they made to these themselves or you something develop another researcher
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Pilot study
Are small scale versions of the study done before the real study which allows researchers to check all aspects of their research, allowing them to make changes to the design, method or allowing them to make changes to the design,method or analysis before the large real version is carried out
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Pilot study advantages
improves the quality of research help, avoid unnecessary work and save time money and effort many changes run through the validity of the findings
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Extraneous variables
| Investigator effects
Anything that the investigator does or says which has an effect on the participants performance in the study. Encourages behaviour from the participant which is not genuine
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How do investigator effects occur
- Certain physical characteristics of investigator may influence the results such age or ethnicity
- less obvious personal characteristics of investigators like accent or tone of voice can influence result participants may pick up on this and not act normal
- investigators may be accidentally bias in the interpretation of the data
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How to deal with investigator affects
| double-blind procedure
- this is where neither participant or investigators know which condition participants are in they are both blind to this knowledge.
- this prevents investigators from accidentally giving participants clues as to what condition they are in therefore reduces demand characteristics
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How to deal with investigator effects
| standardised instructions
All participants are given the same set of instructions to avoid investigator effects caused by different instructions
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Extraneous variables
| demand characteristics
A research effect where participants form impressions of the research purpose and unconsciously alter their behaviour accordingly
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Examples of demand characteristics
- guessing the purpose of the research and trying to please the research by giving the 'right'
- guessing the purpose of the research and trying to annoy the research about giving the wrong results
- acting unnaturally out of nervousness or fear of evaluation
- acting unnaturally due to social desirability bias
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How to deal with demand characteristics
Single-blind procedure this is where participants have no idea which condition of a study they are in
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The reliability of observations
Should be consistent which means that ideally two or more observant should produce the same record. The extent to which two or more observers agree is called inter-rater or inter-observer reliability
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how to improve inter-rater reliability
By creating a behavioural checklist or coding system and training observers and how they should use it
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Ethical issue:
| informed consent how to deal with it
- Participants asked to formally agree to participate agreement should be based on the nature, purpose and their role in the research
- an alternative is to gain presumptive consent
- participants are offered the right to withdraw
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Ethical issue
| informed consent limitations
- Complete information about the nature of the study may change participants behaviour and so low validity of results and purpose of the study
- what people say or expect they will not mind being deceived about may not be true in the situation
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Ethical issue
| deception how to deal with it
- Need for deception should be approved by ethics committee weighing up benefits of the study against costs to participants
- participants should be fully debriefed after the study and offered the opportunity to withhold their data
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Ethical issue
| deception limitations
-Cost-benefit decisions are flawed because they involve subjective judgements and the costs are not always apparent until after the study
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Ethical issue
the right to withdraw
how to deal with it
Limitations
Participants should be informed at the beginning of a study that they have the right to withdraw
- Participants may feel they should withdraw because it will spoil the study
- In many studies participants are paid over awarded in some way so they may not feel able to withdraw
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Ethical issue
protection from harm
how to deal with it
Limitations
- Avoid any risk greater than every day life
- stop the study altogether
-Researchers are not always able to accurately predict the risks of taking part in a study
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Ethical issue
confidentiality
how to deal with it
Limitations
Researchers should not record the names of any participant they should use numbers or false names
It is sometimes possible to work out who the participants were on the basis of the information that has been provided
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Ethical issue
Privacy
how to deal with it
The limitations
- Do not observe anyone without their informed consent unless it is in a public place
- participants may be asked to give their retrospective consent or withhold the data
- no universal agreement about what counts as a public place
- not everyone may feel this is acceptable
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Sampling technique
Opportunity sampling
Definition
Strengths
Limitations
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- Involves selecting participants who are available and willing to take part at the time of investigation researchers.
- it is quick and cost effective
- it is not likely to be representative and therefore findings are not able to be generalised to the target population
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Volunteer/self-selected sampling
Definition
Advantages
Limitations
Involves people volunteering with choosing to participate they do this by responding to adverts of some kind
Is that it is the easiest and most practical method of ensuring a large sample
-sample is unlikely to be representative as people who self select have certain attitudes, more time on their hands and so are in contrast to certain people who would never bother to volunteer or too busy so their opinions are not collected
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Random sampling
definition
strength
limitations
- Where every member of the population has an equal chance to be selected
- Likely to be representative therefore results can be generalised to the target population
- sometimes difficult to get full details of a target population from which to draw a sample
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Quantitative data
| strengths and limitations
- Easier to analyse because data is in numbers
- Produces clear conclusions
-oversimplifies reality and human experiences
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Quantitated data
| Strengths
- Gains access to thoughts and feelings that may not be found using quantitated methods with the closed questions
- provides in depth details of how people behave because participants are given a free range to express themselves
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Qualitative data
| limitations
More difficult to detect patterns and draw conclusions because of the large amount of data collected that is in words not numbers
analysis of data can be affected by personal expectations and beliefs
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Methods of quantitated data
1.measures of central tendency
Mean
strengths and limitations
- most accurate measure because it worked at the interval level of measurement
- includes all the raw scores
- It is less useful if there are extreme scores(very high or low scores)
- Often the final mean school is not any of the original scores
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Methods of quantitated data
1.measures of central tendency
Mode
strengths and limitations
- Sometimes makes more sense than on the measures e.g. the average number of children in a British family is better described to rather than 2.4
- is not useful if there is more than one mode in a set of data
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Methods of quantitated data
1.measures of central tendency
Median
strengths and limitations
- It will not be affected by extreme scores
| - It is less sensitive because it doesn't use all the raw scores
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Methods of quantitated data
2.measures of dispersion
Range
strengths and limitations
- Takes full account of all values including extreme ones
| - It can be distorted by extreme values
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Methods of quantitated data
2.measures of dispersion
Standard deviation
Definition
strengths and limitations
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A measure of The spread of a set of scores from the mean the smaller the standard deviation the better the findings as it shows less variation which indicates that the majority of what is the pants got similar results
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Methods of quantitated data
2.measures of dispersion
Standard deviation
strengths and limitations
- It is more sensitive than the range because all the scores are used in the calculation
- may hide some of the characteristics of the day you were extreme values
