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by: Melanie Maino


Melanie Maino

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Week 7 notes chapter 7 & 8.
Introduction to Research Methods in Psychology
Brianna Stinebaugh
Class Notes
Statistics, measurements
25 ?




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This 5 page Class Notes was uploaded by Melanie Maino on Thursday March 24, 2016. The Class Notes belongs to PSYC314 at Towson University taught by Brianna Stinebaugh in Spring 2016. Since its upload, it has received 10 views. For similar materials see Introduction to Research Methods in Psychology in Psychlogy at Towson University.

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Date Created: 03/24/16
3/21/16   Chapter  7  (continued)   Levels/Scales  of  Measurement   • We  can  evaluate  our  Operational  Definition  by  checking…   o 1)  Reliability   o 2)  Validity   • A  good  O.D.  will  be  both  reliable  and  valid!   • Reliability  focuses  on  consistency  and  making  sure  that  our  measures  and   procedures  are  dependable   o Use  a  measurement  that  has  already  shown  reliability  in  other  studies   • 3  Ways  to  evaluate  reliability   o 1)  Inter-­rater  reliability:  different  observers  measure  the  same   variable  and  see  how  much  agreement  there  is  amongst  the   outcomes/observations.   ▯ Correlation  Coefficient  or  reliability  coefficient  (0.00-­‐1.00)   ▯ Closure  to  1.00  the  stronger  the  agreement  is  with  the  outcome   and  the  least  likely  it  will  be  that  you  have  to  change  your  O.D.   ▯ Ex.  collect  different  individuals  and  fill  out  questionnaire  then   come  together  and  measure  the  reliability  of  the  questionnaire     o 2)  Test-­Retest  Reliability:  we  are  checking  reliability  by  comparing   scores  of  people  who  have  completed  the  same  measure  two  different   times.   ▯ You  can  run  the  same  reliability  coeffient  by  using  two   different  score  from  the  same  individual  if  they  are  highly   correlated  then  you  know  it  worked  if  they  are  poorly   correlated  you  must  change  our  O.D.   ▯ Ex.  give  a  questionnaire  and  then  in  a  couple  of  months  give   the  same  questionnaire  and  you  must  get  the  same  outcome  if   you  are  using  test-­‐retest  reliability.     o 3)  Interitem  Reliability:  I  am  measuring  internal  consistency  amongst   the  test  items.   ▯ Split-­‐half  reliability  analysis  which  splits  your  measure  into   two  halves  and  sees  how  highly  correlated  they  are  to  one   another   ▯ Cronbach’s  Alpha  it  is  a  statistical  analysis  that  picks  one   specific  test  item  and  correlates  it  with  other  test  items  within   your  measure.  If  all  items  are  highly  correlated  then  we  know   we  have  interitem  reliability.   • Validity  is  looking  at  what  we  are  measuring  what  we  intended  to  measure.  It   is  the  accuracy  of  the  measures  we  chose.   o Manipulation  Check:  looks  at  how  valid  our  study  is  going  to  be     • 5  different  ways  to  perform  a  Manipulation  Check...   o Face  Validity:  picking  random  people  and  having  them  judge  how   valid  our  study  appears  to  be  (weakest  technique)   o Content  Validity:  does  the  content  of  our  measures  fairly  reflect  the   content  we  set  out  to  study  and  not  any  other  qualities.   ▯ Ex.  giving  an  exam  that  does  not  reflect  what  you  originally   said  was  going  to  be  on  the  exam  is  low  in  content  validity   o Predictive  Validity:    if  my  measures  are  valid  and  are  accurately   measuring  what  I  intended  to  measure  then  the  procedures  I  choose   should  produce  information  that  allows  us  to  predict  future  behavior.   Want  to  help  human  beings  with  different  psychological  disorders  and   be  able  to  predict  the  future  in  terms  of  those  disorders.   o Concurrent  Validity:  comparing  scores  on  a  measuring  instrument   with  an  outside  instrument  that  has  already  shown  to  be  valid  in   measuring  that  variable  you  are  interested  in.     ▯ Ex.  If  I  created  my  own  IQ  test…if  I  am  trying  to  see  if  my  new   IQ  test  is  valid  I  give  participants  new  and  old  instruments  of   IQ  tests  and  see  how  they  correlate.   o Construct  Validity:  (most  important  way  to  measure  validity)   measuring  transition  from  theory  to  our  current  research  study.  Does   my  new  O.D.  for  this  study  reflect  overall  past  research?  Should  be   consistent!     • 2  Types  of  Validity:  Internal  &  External   • Overall  when  you  want  to  test  of  evaluate  a  study  you  look  at  the   Internal  Validity  and  the  External  Validity   • Internal  Validity…  (3  threats)   o 1-­  Extraneous  Variables:  any  variable  or  factor  that  influences  the   findings  of  my  study  that  aren’t  the  independent  or  dependent   variable.  If  I  have  a  lot  of  extraneous  variables  the  less  controlled  my   study  will  be  (internal  validity  will  be  low).     ▯ Ex.  exercise  vs.  memorization…time  of  day  will  affect  this   o 2-­  Confounding  Results:  error  I  get  from  the  value  of  an  extraneous   variable  that  is  changing  across  my  different  treatment  conditions  and   is  not  my  independent  variable.     o Extraneous  Variables  produce  Confounding  Results   o 3-­  8  classic  threats  to  internal  validity   ▯ 1)  History  threat:  this  is  when  some  situation  or  event  occurs   before  my  experiment  takes  place  that  will  influence  the   results.  Any  outside  events  that  occurring  that  effect  the  results   of  the  study.  Ex.  fender  bender  before  the  study…  (it  is  going  to   be  on  your  mind)   ▯ 2)  Maturation  threat:  any  physical  or  psychological  changes   within  a  participant  that  might  effect  our  dependent  variable.   • 3  instances…  1-­‐  long  study  (drowsiness,  fatigue  or   boredom  influences  change)  2-­‐  longitudinal  studies   (cognitive  and  physical  changes  over  time  that  may   effect  the  dependent  variable)  3-­‐  psyc  101/  intro  to   psyc  students  (gaining  a  lot  of  background  and  may  be   able  to  guess  your  hypothesis)   ▯ 3)  Testing  threat:  threatening  effect  on  our  dependent  variable   from  previous  administration  of  the  same  test.   • Pre-­‐test/post-­‐test  design…     ▯ 4)  Instrumentation  Threat:  when  a  part  of  your  measuring   instrument  changes  during  the  experiment.   • Ex.  an  instrument  breaks  (computer)   • Ex.  handwritten:  measure  each  treatment  condition   equally   • Ex.  written  instruments  (survey)  language  and  wording   of  questions  aren’t  complex  or  complicated  so  when   participants  receive  this  instrument  they  understand   what  they  are  dealing  with   ▯ 5)  Statistical  Regression  Threat:  see  statistical  regression   threat  occurring  when  I  am  grouping  participants  and   assigning  them  to  a  treatment  condition  based  on  an  extreme   score  of  a  test   • ex.  anxiety  vs.  learning  rate:  group  participants  based   on  level  of  anxiety…3  groups  high  anxiety,  medium,  and   low  based  on  scores  on  the  test  you  received.  Coming   into  a  test  not  knowing  what  is  coming  might  spike   somebody’s  anxiety  up.   ▯ 6)  Selection  Threat:  occurs  when  you  don’t  use  random   assignment.   • cannot  control  individual  differences  if  you  are  not   using  random  assignment.   ▯ 7)  Participant  Mortality  Threat:     • 1-­‐  participant  dropout  rate…  why  are  they  dropping  out   of  the  study?   • 2-­‐  longitudinal  study….looking  at  a  elder  and  keep  an   eye  out  for  dementia,  cancers,  death  that  may  effect   your  results.   ▯ 8)  Selection  interaction  threat:  selection  paired  with  any  other   threat  as  a  combination.   3/24/16   Chapter  8-­  Solving  Problems:  controlling  extraneous  variables   • 4  main  Types  of  extraneous  variables:   o 1-­‐  physical  variables   o 2-­‐  social  variables   o 3-­‐  personality  variables   o 4-­‐  context  variables     o If  any  are  present,  internal  validity  is  lowered   • 1)  physical  variables:  any  physical  aspect  of  a  study  where  the  testing   conditions  have  areas  that  need  to  be  controlled   o Ex.  time  of  day,  day  of  week,  environment     o Ex.  testing  concentration  at  8  am     o 3  techniques  to  control  physical  variables:  *start  with  elimination,   then  work  your  way  down  to  balancing   ▯ 1….ELIMINATION  ex.  if  you  are  studying  you  want  to  make   sure  you  are  concentrating  so  you  try  and  eliminate  sound  by   finding  a  quiet  place  to  study   ▯ 2…CONSTANCY  –  physical  variables  are  consistent  within  all   treatment  conditions  with  ALL  participants  ex.  if  you  are   testing  concentration  at  different  times  during  the  day  pick   randomly  from  each  time  slot  while  making  treatment   conditions  so  time  is  spread  out  evenly   ▯ 3…  BALANCING  –  distribute  the  effects  of  an  extraneous   variable  across  all  treatment  conditions  within  the  study   • 2)  Social  variables-­‐  qualities  of  a  relationship  between  the  participant  and   the  researcher  that  can  influence  the  results  of  the  study   o 2  main  social  variables   ▯ 1-­‐  demand  characteristics:  aspect  of  study  that  demands   participants  to  act  in  a  specific  way   • participants  usually  conform  to  how  they  think  they   should  act   • being  a  participant  automatically  alters  behavior,  which   produces  confounding  results   • participants  may  even  try  to  guess  what  you  are   studying   • 2  ways  to  control  demand  characteristics:   o 1…single-­‐blind  studies-­‐  participants  do  not  know   what  treatment  they’re  receiving   ▯ prevents  them  from  guessing  hypothesis   ▯ ex…drug  studies…do  not  know  if  they  are   getting  medicine  or  placebo   o 2…cover  story-­‐  false  explanation  of  procedures   being  used  to  keep  participants  from  guessing   hypothesis   ▯ using  deception-­‐  must  DEBRIEF   participants   • 2-­‐  experimenter  bias-­‐  an  experimenter  can  give   participant  cues  for  how  they  want  them  to  respond   without  realizing  it   o human  and  animal  studies   o Rosenthal  effect-­‐  experimenter  treats   participants  differently,  depending  on  what  is   expected  of  them   ▯ Ex.  giving  the  treatment  condition  who  is   receiving  medicine  more  time  that  the   placebo  treatment  condition   o Experimenter  becomes  the  extraneous  variable   o Can  be  seen  when  experimenter  makes  an  error   recording  notes   o How  to  control  experimenter  bias   ▯ Double-­‐blind  study-­‐  BOTH  the  participant   AND  experimenter  do  not  know  who  is   receiving  which  treatment   • Controls  for  demand   characteristics  and  experimenter   bias   • Use  whenever  possible  because  it   controls  the  most   • 3)  personality  variables:  any  personal  characteristic   that  an  experimenter  brings  to  the  study   o warm  and  friendly  experimenter  get  positive   responses   ▯ less  dropouts   ▯ more  compliance   ▯ better  results   o Hostile/aggressive  experimenters  get  the   opposite   o Have  to  be  consistent  among  treatment   conditions   o Ways  to  control  personality  variables:   ▯ 1-­‐  consistent  as  possible   • write  a  script  to  follow   ▯ 2-­‐  use  multiple  experimenters   • same  number  of  participants   within  each  treatment  conditions   ▯ 3-­‐  minimize  face  to  face  contact  with   participants   o To  control  participant  personality  variables  use   random  assignment     ▯ Every  personality  has  an  equal  chance  of   being  in  each  treatment  condition   ▯ Avoids  selection  threat      


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