Lecture12-February+18th-to+post

Lecture12-February+18th-to+post -  ...

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Unformatted text preview:   Tutorial
quiz
9
due
Today
   Quiz
10
available
today
after
class
   Due
date
is
TUESDAY,
feb
23rd,
before
class
   Exercise
4
will
be
posted
next
week.
Deadline
 will
be
moved
   As
usual…
   3
weeks
left!
Plan
ahead
to
complete
experimetrix
 requirement!
   Mean
=
163
(SD
=
33)
   Range
=
90‐245
   Added
5
points
to
everyone
   Higher
score
is
now
250
   Back
to
experimental
designs…
   Allows
to
establish
cause‐effect
relationships,
 BUT…
   To
be
able
to
do
that
we
need
to
ensure
that
 our
study
has…
   INTERNAL
VALIDITY
   Note
that
we
can
NEVER
prove
causality!
We
can
 only
show
to
what
degree
it
is
PROBABLE!

 1.  2.  Covariation
 Temporal
precedence
 3.  Eliminate
spuriousness
 Measure
other
variables
of
concern
   Ensuring
extraneous
variables
don’t
turn
into
 CONFOUNDS
   Watching violent TV + Acting violent + Living in a violent family Acting violent + Living in a violent family + Watching violent TV   What
it
means
to
establishing
internal
validity?
   Threats
to
internal
validity
   Simple
experiment
   Pretest‐posttest
design
 Method Pros Cons Matching Keeps matched variable constant between conditions • Finding matching participants is difficult • Selection bias (by another variable) Balancing Prevents confounding by the variable • Selection bias (by another variable) Random Produces equivalent Assignment groups Works poorly with small samples Limiting Eliminates some Reduces external validity Populations extraneous variables Nonequivalent groups Subjects may be divided to groups in a biased fashion. History Events may occur between multiple observations. Maturation Participants may become ‘older’ or fatigued. Regression to the mean Subjects may be selected based on extreme scores. Attrition Differential loss of subjects from groups in a study may occur. Testing Taking a pretest can affect results of a later test. Instrumentation Changes in instrument ‘calibration’ or observers may change results.   Other
threats?
   Diffusion
of
treatment
 ▪  Pp
already
have
information
about
study
   Participant
and
experimenter
effects
 ▪  Single
and
double‐blind
experiments
   Sensitivity
of
measure
 ▪  Avoid
floor
and
ceiling
effects
 ▪  Variability
between
scores
necessary
to
detect
 difference!
   Make
sure
groups
are
equal
before
 manipulation
   Balancing,
matching,
etc.
   Make
sure
groups
are
equal
before
 manipulation
   Make
sure
manipulation
actually
works
   Use
a
Manipulation
Check
 ▪  Explicit
measure
of
the

 independent
variable
 ▪  Embedded
questions
 Mood:
Happy
vs.
Sad
 Measure
 mood
after
 Performance
 induction Ask
questions
 Performance
 after
completion 
 
   Make
sure
groups
are
equal
before
 manipulation
   Make
sure
manipulation
actually
works
   Make
sure
to
use
a
good
control
group
   No‐treatment
control
vs.
Placebo
control
   Make
sure
groups
are
equal
before
 manipulation
   Make
sure
manipulation
actually
works
   Make
sure
to
use
a
good
control
group
   Make
sure
to
control
for
PP
and
experimenter
 effects
   Single
and
double‐blind
   Make
sure
groups
are
equal
before
 manipulation
   Make
sure
manipulation
actually
works
   Make
sure
to
use
a
good
control
group
   Make
sure
you
control
for
PP
and
experimenter
 effects
   Make
sure
you
use
a
sensitive
measure
   Check
for
floor
and
ceiling
effects
   Between
vs.
Within
designs
   Between‐Subjects
Designs
   Advantages
and
disadvantages
   Matched‐pairs
design
   Within‐Subjects
designs
   Threats
to
internal
validity
   Minimizing
threats
   Mixed
designs

   Compare
2
or
more
conditions
(control
vs.
 experimental)

   See
if
average
score
on
dependent
measure
(DV)
 differ
between
conditions
   If
differences
exist,
researcher
can
 demonstrate
effects
of
“treatment”
(the
IV)
   Different
groups
of
people
are
exposed
to
the
 different
levels
of
the
IV
and
compared
on
the
 dependent
measure
   IV
manipulated
between
groups
 Group A Words APPLE Group B Words+pics APPLE IV= type of stimulus to be recalled DV= number of words recalled Number of words recalled ? Number of words recalled Do the scores differ?   Different
groups
of
people
are
compared
on
 the
dependent
measure
   e.g.,
the
simple
experiment
   We
can
have
more
than
two
groups
(or
more
than
 one
IV)
 ▪  Groups:
words,
pictures,
words+pics,
etc…
 ▪  IV:
type
of
stimulus,
location
on
screen,
abstract
vs.
 concrete
nouns,
noise
vs.
no‐noise,
incidental
vs.
 intentional
encoding,
etc…..
   Same
group
of
people
is
exposed
to
different
 levels
of
the
IV
and
compared
on
the
 dependent
measure
   IV
manipulated
within
a
group
 Group A Words APPLE + Words+pics APPLE Number of words recalled ? Number of words+ pics recalled Do the scores differ?   Same
group
of
people
is
compared
on
the
 dependent
measure
   IV
manipulated
within
a
group
   Can
have
more
than
one
IV
 ▪  Type
of
event,
memorability
of
event,
etc…
   Between
vs.
Within
designs
   Between‐Subjects
Designs
   Advantages
and
disadvantages
   Matched‐pairs
design
   Within‐Subjects
designs
   Threats
to
internal
validity
   Minimizing
threats
   Mixed
designs

   Each
individual
has
one
score
   If
we
have
30
scores
from
group
A
and
30
from
 group
B
=
study
has
60
participants
   As
many
groups
as
the
levels
of
the
IV
   Can
be
experimental
or
quasi‐experimental
   E.g.,
When
IV
is
a
participants
variable
   Can
compare
more
than
2
groups
   Advantages
   Scores
are
independent
of
other
scores
   Always
an
option
when
comparing
treatment
 conditions
   Disadvantages
   Need
large
number
of
participants
   Existing
Individual
differences
(non‐equivalent
 groups)
 ▪  Can
turn
into
confounds
 ▪  Can
mask
treatment
effects
   Matched‐Pairs
design
 Control   Pro:
Reduce
error
variance
   Con:
need
a
large
pool
of
people
 Experimental   Between
vs.
Within
designs
   Between‐Subjects
Designs
   Advantages
and
disadvantages
   Matched‐pairs
design
   Within‐Subjects
designs
   Threats
to
internal
validity
   Minimizing
threats
   Mixed
designs

   Same
sample
of
individuals
participates
in
all
 the
treatment
conditions
   AKA
repeated
measures
design
   Advantages
 Increased
ability
to
detect
treatment
effects
 ▪  Decrease
random
error
due
to
Individual
differences
   Need
less
participants
   But…..

   Disadvantages

   Time‐related
threats
 ▪  History
 ▪  Maturation
 ▪  Attrition
 ▪  Instrumentation
   Disadvantages

   Time‐related
threats
   Order
Effects
 ▪  Variations
in
response
behavior
due
to
order
of
 conditions
 ▪  Decrease
internal
validity
   Practice
effect
   Performance
improves
on
later
measures
   Minimize
with
practice
prior
to
experiment
   Fatigue
effect
   Performance
declines
on
later
measures
   Minimize
with
shorter
&
interesting
tasks
   Treatment
Carryover
effect
   Earlier
treatment
affects
later
treatment
   Minimize
by
increasing
time
between
treatments
   Sensitization
effect
   Performance
changes
due
to
hypothesis
guessing
   Minimize
by
preventing
participants
from
noticing
 treatment
changes
   Reduce
number
of
conditions
   Change
sequence
of
conditions
   Randomized
Within‐Subjects
   Randomized
blocks
   
Counterbalanced
Within‐Subjects
   Reduce
number
of
conditions
   Change
sequence
of
conditions
   Randomized
Within‐Subjects
   Randomized
blocks
   
Counterbalanced
Within‐Subjects
 ▪  Latin‐square
design
 ▪  Matrix
of
n
elements
were
each
element
appears
 exactly
once
in
each
column
and
in
each
row
   A
study
that
combines
between‐
and
within‐
 participants
designs
   One
variable
‘within’

   One
variable
‘between’
 Within Memorability High experimental training control Between Low Number of Number of correct rejection correct rejection Number of Number of correct rejection correct rejection ...
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