ohth 2160 research in health sciences--design and hypothesis testing

5/23/2018 OHTH 2160 Research in Health Sciences--Design and Hypothesis Testing

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Discipline of PsychologySchool of Health Sciences

Research in Health Sciences 2013

OHTH 2160

GOALS FOR THIS TOPIC

Understand the essential differences between

experimental, quasi-experimental and non-experimentaldesigns, in terms of their design characteristics and thetypes of questions that each type of design can answer.

Understand why experimental research is so important

and so highly regarded, particularly in the context ofintervention research.

Understand the four essential defining characteristics of

true experiments Understand why quasi-experiments are not true

experiments, and what this means in terms of answeringresearch questions.

Understand sources of variability in data and the concept

of internal validity, in terms of control groups and researchdesign.

Understand the logic underlying null hypothesissignificance testing.

Define and explain reliability and validity.

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2asic esearch Design and 3ypothesis 4esting

Hypothetical study:

Does exposure to violent videos lead to higher levels of

aggressive play in young children?

4otal N5 *& 6n5 (* in each group7

Experimental group+ 8atch violent videosControl group+ 8atch neutral videos

9ideotaped playing together after exposure tovideos and level of aggressive play recorded.

:.9.+ 4ype of video material

4wo levels+ 9iolent and neutral

D.9.+ ;evel of post-video aggression

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Operationalised as+




Children who watch violent video material will exhibit

higher levels of post-viewing aggressive play than

children who watch neutral content videos.

$alsifia"ility+ @ir Aarl !opper.

:t is possible to prove statements%hypotheses "&&B

false, but impossible to prove them "&&B true.

?ll crows are blacE

Fou can falsify statements, but not questions.

8hat colour are crowsGE @o whatG

Next Step C!llecti!n !" ra# $ata%

Descriptive statistics:?im to capture the essential featuresof the results in an easily comprehensible form.

Hraphical display




9iolent video group+ %5 '.1', &D5 (.&&




". :s there a statistically significantdifference between thetwo groupsG

(. 8hat do these results this tell us about our hypothesisGDo these results support, or fail to support ourhypothesisG

). ?re these sample results an accurate reflection of what=sgoing on in thepopulationG

8hen we test a hypothesis statistically, we want to

reach some conclusion about what=s going on in ourpopulationof interest, and we use our sampledata toreach that conclusion. 4his is called estimation orinference.

8hyG Lur results have greater importance and

relevance if we can generalise them to the population atlarge, and not ust limit them to our sample. 8e want tobe able to mae statements about what=s going on inthe world at large.

$irst (ey concept+

out there in the population at large there are true

population means for these variables 6calledparameters7.

:f : were able to bring every child in the )orld into my

lab and subect them to this experiment, : would nowthe true population mean, the mean for everybody.

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8e can never really (no) what the true population

mean is, because we can never actually test a )hole

population.

:nstead, we have to test a small section of that

population, which we call the sample.

2ased on the results of that sample, we mae an

educated guessE 6called an estimate or inference7

about the population mean, and our "estguess aboutthe value of thepopulationmean is the samplemean.

egardless of what the true population mean is, there is

al)ays the li(elihoodthat : will get a sample mean thathas a different valuefrom the population mean, si,pl&$-e t! chance.

4he difference between the mean of my sample and the

corresponding mean in the population is calledsa,plin' err!r, and it is a chance event.

8e hopethat by selecting our sample in a truly random

fashion that we minimise the level of sampling error, but

it=s always a threat hanging over us.

@maller samples have a greater lielihood of sampling

error than larger samples.

@o, to understand hypothesis testing, the first concept

to understand is the concept of sampling error, and the

fact that sampling error happensby chance.

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&econd (ey concept+

8hen we carry out a statistical hypothesis test, wehave to mae a choice, based on our sample results,concerning two competing possibilities.

Null hypothesis5 our samples come from populations

where there is no difference between the populationmeans.

:f : were able to test the )hole population, : would find

that the population means for each of these groupswould be the same.




8e do this by testing the null hypothesis only 6the

alternative hypothesis doesn=t come into calculations7,and what we try to do isprove that the null hypothesisis )rong.

:n statistical terms, we try to re+ectit.

:f we decide to reect the null hypothesis, then )e are

forced to accept the alternative.

4he logic that we follow to do this is as follows+

". 8e assume that the null hypothesis is true

(. >ven when there=s no true difference in the population6i.e., null hypothesis true7, we accept that our samplemeans may hint that there=s some difference, simply dueto chance 6sampling error7

). 8e as the question+ 3ow liely is it that : could get myobserved sample result +ust "y chance, even if there=s

really no difference in the populationG

1. :f the lielihood of your observed sample meansoccurring by chance alone is less than *B 6.&* inprobability terms7, then we conclude that the nullhypothesis is wrong, we re+ect it, and we accept thealternative hypothesis

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*. 8e conclude that there is a statistically significantdifference between the two groups.

4he value that we base our decision on is called the

significance levelorplevel.

:f the p level is less than .&*, then we reect the null

hypothesis.

&ignificance level+ 4he probability that your observed results have

occurred by chance.

*ll statistical hypothesis tests generate a p level,

regardless of the type of research you are doing.

4his logic applies to all significance testing, regardlessof the area and regardless of the statistical test beingused.

t-tests 6independent and related%matched samples7

Used to answer the question+ :s there a

significant difference between two meansG

Correlation, r


significant relationship between twovariables?

2

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significant relationship between the countsE

associated with two variables.

e,!nstratin' i""erences in esi'nThree h&p!thetical in$ii$-al $i""erence st-$ies

,' Does alcohol change people!s personality?

*& people are recruited for a study. 4hey are randomlyallocated to two conditions+ alcohol and placebo control.4hey complete a standardised personalityquestionnaire before consuming a beverage. 4hey thenconsume a large amount of either alcohol or an inertplacebo control. 4wo hours later, they complete analternate form of the personality questionnaire.

' *re )omen more .sensation see(ing/ than men?

*& men and *& women are administered a standardisedsensation-seeing scale. 4he scores are compared.

0' hat is the relationship "et)een scores on a

standardised paper-and-pencil personalityquestionnaire and the overt "ehavioural expression ofpersonality characteristics?

? large group of people are administered astandardised personality questionnaire, such as the>ysenc >!M. 4hen behavioural correlates of the

personality variables are measured. or example, for

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extraversion, the number of times each personsocialises at night is recorded. or neuroticism, thenumber of times a person cries is recorded. 4he studyis investigating the nature of the relationship betweenstandardised measures of personality, and thebehavioural expression of those measures.

4he "ststudy is experimental+

h&

:t has an experimental group and a control group.

:t involves random allocation of participants to groups.

:t has clearly defined independent and dependent

variables.

4he levels of the independent variable are under the

control of the investigator.

h& hae a c!ntr!l 'r!-p

4he control group provides a baseline against which

we can assess the impact of the treatment on theexperimental group.

Control groups should be treated the same as the

experimental group in every way but the treatment.

:f we don=t have a control group, we can=t isolate theeffect of the treatment from the effect of otherinfluences 6sources of error that might compromisethe internal validityof the design7.o @ources of error are any other factors that might

influence a participant=s score on the dependentvariable, apart "r!, the treat,ent%

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here Does the 1aria"ility Come $rom in an ExperimentalDesign?

8ithin-group variability 2etween-group variability

hat Causes Error in a 2esearch Design?

:ndividual differences

>xperimental error

hy randomly allocate? 2ecause it maximises the probability that other

influences 6called sources of error7 are randomlyspread among the groups.

or example, what if everyone in the treatment group

was over *& years old, and everyone in the controlgroup was under (*G Lr if everyone in the control

group was female and everyone in the experimentalgroup was male.

Fou wouldn=t be able to separate out the effect of the

treatment from the influence of age or sex. 4heinfluence of the treatment would be said to beconfoundedby the systematic errorassociated with ageor sex.

andom allocation maximises the probability that thisdoesn=t happen.

3ndependent varia"le+ Hrouping variable. Under the

control of the investigator.

Dependent varia"le+ @core, outcome, or thing being

measured.

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Whats so great aout e"peri#ental designs$

4hey are the only design that permits you to mae

cause and effect statements about the relationshipbetween the independent and dependent variables.

9ery important in intervention research.

Ho) could this "e study have "een done differently?

>ach person could have participated in both phases of

the study

o epeated measures or within-subects design. !articipants could have been matched on personality

characteristics before being allocated to either theexperimental or control groupo Iatched samples design.

2oth of these designs reduce sources of error, and

therefore result in any treatment effect being morenoticeable 6error clouds treatment effects4 and issomething )e try to reduce7.

nd&tudy

Muasi-experimental design.

Hroups are based on pre-existing characteristic of

the participants. ?ll sex difference studies are quasi-experimental. @ome studies can only be done using aquasi-experimental approach.

Cannot randomly allocate, because the participants

allocate themselves.




?nalyse results in the same way as for an

experimental study.

0rd&tudy

Correlational 6non-experimental7




2o-2o doll experiment+

http+%%www.youtube.com%watchGv5FclN2hn1&hU

Children see, children do

http+%%www.youtube.com%watchGv5#Jf32(cruJU

!lacebo story on #& minutes

http+%%www.youtube.com%watchGv52D?f$HtUrM

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http://www.youtube.com/watch?v=YclZBhn40hUhttp://www.youtube.com/watch?v=6JfHB2cruJUhttp://www.youtube.com/watch?v=BDAf8GtUr7Qhttp://www.youtube.com/watch?v=YclZBhn40hUhttp://www.youtube.com/watch?v=6JfHB2cruJUhttp://www.youtube.com/watch?v=BDAf8GtUr7Q

ohth 2160 research in health sciences--design and hypothesis testing

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