Nonexperimental Quantitatiwve Research

8/18/2019 Nonexperimental Quantitatiwve Research

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Nonexperimental

QuantitativeResearch


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Defnitions

Defning characteristic o experimentalresearch: manipulation o independent variable.

Defning characteristic o nonexperimentalresearch: lack of manipulation o independent

variable. Researcher studies what naturally

occurs or has already occurred.

Thereore, no random assignment

Can be used to suggest causality but not to


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eps n onexper men aResearch

. Determine the research problem andhypotheses to be tested.

-. elect the variables to be used in the study.

/. Collect the data.

0. naly1e the data.

2. (nterpret the results.

.%atch out or the post hoc allacy 3arguing, aterthe act, must have caused ' because youobserved in past that preceded '4.

.5ost hoc or inductive reasoning useul, but ater


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Independent Variables inNonexperimental Research

Categorical (!s that cannot be manipulated:gender, parenting style, learning style,ethnicity, retention in grade, personality type,drug use.

6uantitative (!s that cannot be manipulated:intelligence, age, 75, personality trait

operationali1ed as 8uantitative 3e.g., level osel9esteem4, leadership style

hould not categori1e 8uantitative independent variables


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Simple Cases o Causal-Comparative Correlational

Consider simple cases 3only two variables4 asstarting point. They are awed designs needingimprovement.

. imple case o causal9comparative 9 onecategorical (! 3gender4 and one 8uantitativeD! 3e.g., perormance on a math test4.

Chec+ or di;erence between groups. (s di;erence statistically signifcant&

tatistical signifcance 9 di;erence betweengroup means probably not


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-. imple case o correlational 9 one quantitative (! 3level o motivation4 and one 8uantitativeD! 3perormance on math test4.

o.Chec+ correlation coe;icient.

o.(s observed correlation statistically signifcant3not due to chance4&

o.Correlation coe;icient detects linear 3not

curvilinear4 relationships.


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/. 'oth simple cases o nonexperimentalseriously awed i want to ma+e causalconclusion 3(! D!4.

.>bserving relationship not su;icient.

0. imple cases can be improved:

.Control or extraneous variables.

.?se longitudinal studies..Test theoretical models.

.'ut remember: randomi1ed experiments best

or documenting cause and e;ect.


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!ppl"in# Necessar" Conditions or Causation in Nonexperimental

@onexperimental research is much wea+er than strongexperimental and 8uasi experimental research.

Condition : observe relationship. Di;icult to establish conditions - and / 3especially /4.

Condition -: use logic and theory 3biological sex occursbeore achievement4 and design approaches3longitudinal4.

Condition / is serious problem in nonexperimental

research Relationship might be AspuriousA 3non9causal= due to

conounding extraneous variable4.

Condition /: use logic and theory 3list extraneous


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responding to a fre and the amount o fre damage& There is a relationshipbetween those two variables 3the more fre truc+s, the more the fredamage4. >bviously this is not a causal relationship 3i.e., it is a spuriousrelationship4. (n igure below, you can see that ater we control or the si1eo fre, the original positive correlation between the number o fre truc+s

responding and the amount o fre damage becomes a 1ero correlation 3i.e.,no relationship4. The original relationship disappears.


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!ppl"in# Necessar" Conditions or Causation in Nonexperimental

(mportant idea: how to control or a variable. @umber o fre truc+s responding to fre and fre

damage are correlated.

Relationship is spurious.

ee igure in next slide: i control or si1e o fre,

original positive correlation reduces to 1ero 3norelationship4.

t each level o fre si1e, no relationship between

number o fre truc+s and fre damage.


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onexper men a

ResearchTo$ Terms%T"pes&'

Causal comparative research

Correlational research


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ausa - ompara ve

Research lso called #*x 5ost acto$ research, meaning #aterthe act$ or #retrospectively$

*xplanatory @on9experimental Design"also called a

#natural experiment$

There is a control or comparison group

(ntact groups are used

The treatment is not manipulated( it has alread"

occurred)


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ausa - ompara ve

Research

ocuses frst on the e;ect, then attempts todetermine what caused the observed e;ect. *xamples: Do high school drop9outs di;er rom high school

completers in reading achievement& re men better atmath than women&

(ndependent variable is typically categorical 3e.g.,

high school students who dropped out versusstayed in school4 with two or more levels, public vs. private sector

imple causal9comparative designs have one (!and one D!, though they can be more complex

t


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ausa - omparat ve esearc

-Topics

(nterest is in C*>s lie satisaction%hat would a good reerenceEcomparison

groups be&

7roup o interest is drop9outs rom the T7school o 'usiness F' program

%hat would a good comparisonEreerencegroup be&


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Causal-Comparative Research - *lannin#

o elect groups that are similar as possible on all but the variable o interest

o e.g., library patronEnonpatron= vegans E non9vegans

o Careul selection o the reerence group

o ?se several comparison groups

o e.g., select groups on a second or third variable

such as gender, *, ethnicity, experienceo elect relevant D!s

o Try to minimi1e conounding variables

o Try or random sample


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Causal-Comparative Research - +imitations

Theres always another variable that could be the#third$ variable that causes the e;ect

Review G three conditions or causality

7roups are always none8uivalent"so always havedi;erential selection

@eed to be exceedingly careul in ma+ing anystatements about potential cause

Di;iculty in establishing precedence o cause 3e.g., didlow sel9esteem lead to dropping out or did droppingout lead to low sel9esteem&4


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Correlational Desi#ns

5assive, observational design

Distinguish correlational designs versuscorrelation as a statistic

5urpose is to explore or predict and also to

generate potential explanations o cause9e;ectrelationship

6uantifes strength and direction o relationships

between two or more variables


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Correlational Desi#ns

*xamples: Does sel9esteem correlate withacademic achievement& Does resiliencypredict success in school&

@o group assignments or divisions

@o strong conclusions regarding cause, thoughthis is debatable

Can analy1e large number o variables in a

single study


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-

Topics• Try this:

• Bow can we assess the e;ects o an T

training course via a correlational study&

• nother example:

• re therapist empathy and therapistperceptions o client progress related& %hatwould we need to consider&

t D


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orre at ona Des #ns-

*lannin#

(dentiy variables that might be determinants o the behavioro interest

(dentiy other variables that might a;ect interrelationships

(dentiy sub


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on t ons to ,sta s

Causationa. The cause and e;ect must be correlated.

a. ssociation

b. The cause must ta+e place beore the e;ect.a. Temporal precedence

c. The casual relationship still exists ater thetwo are isolated rom all other variables.

a. (solation

C l C ti C l ti l


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Causal-Comparative Correlational'

Improvement

(. @onexperimental research is much wea+er thanstrong experimental and 8uasi experimental research.

((. Control or extraneous variables.

(((.?se longitudinal studies.

(!. Test theoretical models.

!. 'ut remember: randomi1ed experiments best ordocumenting cause and e;ect.

!ppl"in# Necessar" Conditions


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!ppl"in# Necessar" Conditions

or Causation in Nonexperimental

Condition ' observe relationship.

Di;icult to establish conditions - and / 3especially /4.

Condition .' use logic and theory 3biological sex occursbeore achievement4 and design approaches 3longitudinal4.

Condition /' is serious problem in nonexperimentalresearch

Relationship might be AspuriousA 3non9causal= due toconounding extraneous variable4.

Condition /' use logic and theory 3list extraneous variables and measure4, control techni8ues 3statisticalcontrol, matching4, and design approaches.

T h i C t l i


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Techni0ues o Control in

Nonexperimental

) 1atchin#)• trategy: identiy #matching variableA

3gender, income, intelligence4 and

e8uate groups on it.

• Di;erence between groups cant be

because o matching variable becausehas been #controlled or.$

• 5roblem: cant thin+ o all extraneous

T h i C t l i


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Nonexperimental

.) 2oldin# extraneous variableconstant)

• trategy: identiy extraneous variableand conduct study with people romsingle level.

• *xample: hold gender constant byresearching only women.



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Nonexperimental

/) Statistical control)

oComputer program examines relationship between(! and D! at each level o variable control or.

o*artial correlation 9 correlation between two8uantitative variables ater controlling orextraneous variable.

o !nal"sis o covariance 9 relationship betweencategorical (! and 8uantitative D! atercontrolling extraneous variable.


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Desi#ns

Two +ey dimensions inconstructing nonexperimental

research designs:

Time dimension

Research ob


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Classi"in# Nonexperimental b" TimeDimension

@onexperimental research classifed accordingto time dimension:

. Cross9sectional G data collected at singlepoint in time,

'. Hongitudinal or prospective G data collected

in orward direction at two or more timepoints 3moving orward4

C. Retrospective G data collected loo+ing

bac+ward or rom past.

Depiction of Cross Sectional Longitudinal & Retrospective Research Designs


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Desi#n

T"pe

Depiction ,xample

Cross-

sectional

O Data are collected at one pointin time on several variables

such as gender, income, and

education

+on#itudinal O O. ) ) )

>n Data are collected in a

orward direction over time on

one or more variables such as

gender 3>4, (6 3>4,

discipline problems in middle

school 3>4, high school 75

3>-4 and dropout status 3>-4.

Retrospectiv

e

OT4n ) ) ) OT4 OT Data are collected thatrepresent present and past

status on variables such as

dropout, use o drugs, and

75.

> stands or collection o data on independent variables, controlvariables, andEor dependent variables. n stands or the fnal timeperiod data are collected or the longitudinal design, T stands or thecurrent time, TG stands or a time in the past, and TGn stands or

Depiction of Cross-Sectional, Longitudinal, & Retrospective Research Designs


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Classi"in# Nonexperimental b"Research Ob5ective Dimension

@onexperimental conducted or many reasons.Three ma


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Classi"in# Nonexperimental b"Research Ob5ective Dimension

Causal modelin# G constructing theoreticalmodels and testing with new data. Commonlyused in nonexperimental research.

tudy direct e;ect 3e;ect o one variable onanother4: I J

tudy indirect e;ect 3e;ect o variable onanother through intervening or mediator

variable4: I ( J

trength o causal modeling: based on theoryand theory testing.


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Classi"in# Nonexperimental b"Time Research Ob5ective

To classiy nonexperimental,


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Nonexperimental Quantitatiwve Research

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