I would like a quote on research method paper. attached are the results of spss, method section and 3 articles for reference. there are 5 but could only upload the 3. Thank you for your time
Perceptions of Sexual Harassment (SH) METHODExperiment 2 GENERAL INSTRUCTIONS FOR METHOD SECTION • Have sufficient information to replicate the study. • Follow logical progression of idea in each subsection. • Do not omit crucial information! • Do not mix sections! PARTICIPANTS • Total N (n male, n female) • Recruited using a Convenience sample • Age range (mean age if given) • Ethnicity: List each category with % • Marital status: List each category with % • Sexual orientation: List each category with % • Highest degree or level of education: List each category with % • Years of work experience: List each category with % • English-speaking adults • No incentives • All participants were treated in accordance with the Ethical Principles of Psychologists and Code of Conduct (American Psychological Association, 2002) MATERIALS • Two Qualtrics questionnaires (SH QQ1 and SH QQ2) • Informed consent (briefly describe) • Demographic questions(briefly describe) • Instructions (briefly describe) • SH scenarios – 10 vignettes adopted and modified from Terpstra and Baker (1987) • Two sets of vignettes depicting different sexual harassment scenarios • Male perpetrator, female victim (MPFV) • Male perpetrator, male victim (MPMV) • Two counterbalanced testing order: MPFV before MPMV, and MPFV after MPMV • Counterbalancing technique was used to control for potential sequencing or carryover effects from one type of gender pairing to the other type • Debriefing Statement (briefly describe) MATERIALS • Vignettes • Associated with each vignette - • The Likert-type scale • Used by participants to rate degree of severity • Scale range from - 1 (not at all harassing) to 7 (extremely harassing) • For each set of vignettes • Participants’ responses to the 10 severity items were averaged yielding a mean score ranging from 1 to 7 • 1 (perceived as low severity) • 7 (perceived as high severity) PROCEDURE Tested individually using online Qualtrics questionnaires. SHQQ1 and SHQQ2 randomly distributed Approximately equal number of males and females for each Qualtrics questionnaire. Read the informed consent form, provided consent to participate, and answered demographic questions Carefully read and rated each SH vignette Thanked and debriefed DESIGN AND DATA ANALYSIS 2 x 2 mixed factorial design 2 Independent variables IV 1 – “Gender of victim” depicted in the scenario , 2 levels (male or female) Within-subjects variable True independent variable IV 2 – “Gender of participant” who responded to the scenario , 2 levels (male or female) Between-subjects variable Quasi-independent variable Dependent variable “Severity of sexual harassment” perceived/rated by participants (ranged from 1 to 7). METHOD – REVIEW OF IMPORTANT CONCEPTS RELATED TO THE DESIGN • Do Not Put this in your method section • What is a mixed factorial design? • A mixed design includes a within-subjects independent variable and a between-subjects independent variable • What is a within-subjects independent variable? What is a between-subjects independent variable? • If each subject is repeatedly tested under all conditions/levels of an independent variable, one at a time, then we say the independent variable is a within-subjects variable • “(gender of victim) depicted in the test scenario” • If a subject is tested just one time, under one condition/level of an independent variable, then we say the independent variable is a between-subjects variable • “(gender of participants) who responded to the scenario.” METHOD – REVIEW OF IMPORTANT CONCEPTS RELATED TO THE DESIGN • Do Not Put this in your method section • What is a true independent variable? What is a quasi-independent variable? • A true independent variable is a variable that can be manipulated by an experimenter. • The first independent variable (gender of victim) depicted in the test scenario is a “true” independent variable. • It is a true-independent variable because it can be precisely manipulated by a researcher. • A quasi-independent variable is a variable that cannot be manipulated; it is a variable on which groups of participants naturally differ. • The second independent variable (gender of participants) who responded to the scenario is a “quasi” independent variable. • It is a quasi-independent variable because it is a variable on which groups of participants naturally differ. • A researcher cannot manipulate a quasi-independent variable (like “gender of participants”). DESIGN AND DATA ANALYSIS Two-way analysis of variance (ANOVA) Main effect of gender of victim on severity of sexual harassment Main effect of gender of participant on severity of sexual harassment Interaction effect between gender of victim and gender of participant on severity of sexual harassment Two correlated-samples t-tests—Compare mean ratings of the MPFV scenarios with mean ratings of the MPMV scenarios One for male participants One for female participants Criterion for significance was p <.05 perceptions="" of="" sexual="" harassment="" (sh)="" perceptions="" of="" sexual="" harassment="" results="" fall="" 2021="" psyc="" 3311="" lab="" demographic="" data="" for="" the="" participants="" section="" number="" of="" participants="" n="323" n="" %="" gender="" male="" 147="" 45.5%="" female="" 176="" 54.5%="" demographic="" data="" for="" the="" participants="" section="" n="" %="" age="" 18="" to="" 29="" years="" old="" 234="" 72.4%="" 30="" to="" 39="" years="" old="" 51="" 15.8%="" 40="" to="" 49="" years="" old="" 24="" 7.4%="" 50="" to="" 59="" years="" old="" 8="" 2.5%="" 60+="" years="" old="" 6="" 1.9%="" demographic="" data="" for="" the="" participants="" section="" n="" %="" ethnicity="" american="" indian="" or="" alaska="" native="" 1="" 0.3%="" asian="" or="" asian="" american="" 12="" 3.7%="" black="" or="" african="" american="" 22="" 6.8%="" hispanic="" or="" latino="" 214="" 66.3%="" native="" hawaiian="" or="" pacific="" islander="" 4="" 1.2%="" white="" or="" caucasian="" 11="" 3.4%="" other="" 59="" 18.3%="" demographic="" data="" for="" the="" participants="" section="" n="" %="" marital="" status="" single="" 234="" 72.4%="" married="" 60="" 18.6%="" living="" common="" 16="" 5.0%="" separated="" 3="" 0.9%="" divorced="" 8="" 2.5%="" widowed="" 2="" 0.6%="" demographic="" data="" for="" the="" participants="" section="" n="" %="" sexual="" orientation="" heterosexual="" 284="" 87.9%="" homosexual="" 11="" 3.4%="" bisexual="" 26="" 8.0%="" missing="" 2="" 0.6%="" demographic="" data="" for="" the="" participants="" section="" n="" %="" education="" some="" high="" school="" 3="" 0.9%="" high="" school="" 44="" 13.6%="" some="" college,="" no="" degree="" 124="" 38.4%="" associate="" degree="" 67="" 20.7%="" bachelor’s="" degree="" 72="" 22.3%="" master’s="" degree="" 9="" 2.8%="" other="" 4="" 1.2%="" demographic="" data="" for="" the="" participants="" section="" n="" %="" work="" experience="" none="" 15="" 4.6%="" less="" than="" one="" year="" 15="" 4.6%="" 1="" to="" 2="" years="" 37="" 11.5%="" 3="" to="" 4="" years="" 56="" 17.3%="" 4="" to="" 5="" years="" 30="" 9.3%="" 5+="" years="" 170="" 52.6%="" demographic="" data="" for="" the="" participants="" section="" n="" %="" victim="" of="" sexual="" harassment="" yes="" 145="" 44.9%="" no="" 178="" 55.1%="" revisiting="" the="" design="" 2="" x="" 2="" mixed="" factorial="" design="" the="" first="" independent="" variable="" “gender="" of="" victim”="" depicted="" in="" the="" test="" scenarios="" (within-subjects)="" female="" male="" the="" second="" independent="" variable="" “gender="" of="" participant”="" who="" responded="" to="" the="" test="" scenarios="" (between-subjects)="" female="" male="" revisiting="" the="" hypotheses="" •="" hypothesis="" 1:="" it="" is="" hypothesized="" that="" there="" will="" be="" a="" significant="" main="" effect="" for="" gender="" of="" victim.="" scenarios="" with="" male="" perpetrators="" and="" female="" victims="" (mpfv)="" will="" be="" viewed="" as="" more="" severely="" harassing="" than="" similar="" scenarios="" with="" male="" perpetrators="" and="" male="" victims="" (mpmv).="" evaluate="" the="" outcome="" regarding="" the="" main="" effect="" of="" the="" first="" independent="" variable="" “gender="" of="" victim”="" on="" the="" dependent="" variable="" “severity="" of="" sexual="" harassment.”="" revisiting="" the="" hypotheses="" •="" hypothesis="" 2:="" it="" is="" also="" hypothesized="" that="" there="" will="" be="" a="" significant="" main="" effect="" for="" gender="" of="" participant.="" compared="" to="" males,="" females="" will="" view="" scenarios="" depicting="" sexual="" harassment="" as="" more="" severely="" harassing.="" evaluate="" the="" outcome="" regarding="" the="" main="" effect="" of="" the="" second="" independent="" variable="" “gender="" of="" participant”="" on="" the="" dependent="" variable="" “severity="" of="" sexual="" harassment.”="" revisiting="" the="" hypotheses="" •="" hypothesis="" 3:="" finally="" it="" is="" hypothesized="" that="" there="" will="" not="" be="" a="" significant="" interaction="" effect="" between="" the="" gender="" of="" victim”="" and="" the="" gender="" of="" participant="" on="" the="" severity="" of="" sexual="" harassment.="" for="" both="" female="" participants="" and="" male="" participants,="" scenarios="" involving="" male="" perpetrators="" and="" female="" victims="" (mpfv)="" will="" be="" viewed="" as="" more="" severely="" harassing="" than="" similar="" scenarios="" involving="" male="" perpetrators="" and="" male="" victims="" (mpmv).="" •="" evaluate="" the="" outcome="" regarding="" the="" interaction="" effect="" between="" the="" first="" independent="" variable="" “gender="" of="" victim”="" and="" the="" second="" independent="" variable="" “gender="" of="" participant”="" on="" the="" dependent="" variable="" “severity="" of="" sexual="" harassment.”="" m="" ea="" n="" s="" ev="" er="" it="" y="" r="" at="" in="" g="" gender="" of="" participant="" female="Male" =="" 3.5="" 1="" gender="" of="" victim="" male="" female="" 7="" scoring="" and="" analysis="" •="" for="" each="" set="" of="" vignettes="" (the="" mpfv="" vignettes="" or="" the="" mpmv="" vignettes),="" participants’="" responses="" to="" the="" 10="" severity="" items="" were="" averaged="" yielding="" a="" mean="" score="" that="" could="" range="" from="" 1="" to="" 7.="" high="" scores="" indicated="" perceived="" high="" severity;="" low="" scores="" indicated="" perceived="" low="" severity.="" •="" a="" two-way="" anova="" for="" mixed="" designs="" was="" used="" to="" test="" the="" proposed="" hypotheses.="" •="" moreover,="" two="" correlated-samples="" t-tests="" were="" conducted="" to="" compare="" ratings="" of="" the="" mpfv="" scenarios="" with="" ratings="" of="" the="" mpmv="" scenarios.="" one="" for="" the="" male="" participants;="" the="" other="" for="" the="" female="" participants="" •="" a="" significance="" level="" of="" p="">< .05 was adopted to conclude statistical significance for the results results summary mean (standard deviation) the first independent variable “gender of victim” depicted in the test scenarios (within-subjects) female male the second independent variable “gender of participant” who responded to the test scenarios (between-subjects) female m=6.08 sd=(.79) 5.98 (.87) 6.03 (.80) male 5.83 (1.06) 5.73 (1.11) 5.78 (1.06) 5.97 (.93) 5.87 (.99) results report statistics in text: f ratio f (df-between, df-within) = xxx, p = xxx, partial η 2 = xxx example: f (2, 177) = 6.39, p = ,002, partial η2 = .07 t value t (df) = xxx, p = xxx. example: t (df) = 3.51, p = .001. d = 0.65 df = degrees of freedom note: partial eta-squared (partial η2) is a way to measure the effect size of different variables in anova. suggested norms for partial eta-squared: small = 0.01; medium = 0.06; large = 0.14. results (related to hypothesis 1) • there was a significant main effect of gender of victim on severity of sexual harassment, f (df gender_v, df error) =____, p=___, partial η2 =___. scenarios with male perpetrators and female victims (mpfv: m =___, sd = .___) were perceived as more severely harassing than similar scenarios with male perpetrators and male victims (mpmv: m = ___, sd = ____)(see table 1). (note: see slide 15 for the corresponding means and standard deviations. use means and standard deviations for total male and female victims) results (related to hypothesis 2) • write the results related to hypothesis 2 according to statistical data given above (note: see slide 15 for the corresponding means and standard deviations. use means and standard deviations for total male and female participants) results (related to hypothesis 2) • there was a significant main effect of gender of participants on severity of sexual harassment, f (df gender_p,df .05="" was="" adopted="" to="" conclude="" statistical="" significance="" for="" the="" results="" results="" summary="" mean="" (standard="" deviation)="" the="" first="" independent="" variable="" “gender="" of="" victim”="" depicted="" in="" the="" test="" scenarios="" (within-subjects)="" female="" male="" the="" second="" independent="" variable="" “gender="" of="" participant”="" who="" responded="" to="" the="" test="" scenarios="" (between-subjects)="" female="" m="6.08" sd="(.79)" 5.98="" (.87)="" 6.03="" (.80)="" male="" 5.83="" (1.06)="" 5.73="" (1.11)="" 5.78="" (1.06)="" 5.97="" (.93)="" 5.87="" (.99)="" results="" report="" statistics="" in="" text:="" f="" ratio="" f="" (df-between,="" df-within)="xxx," p="xxx," partial="" η="" 2="xxx" example:="" f="" (2,="" 177)="6.39," p=",002," partial="" η2=".07" t="" value="" t="" (df)="xxx," p="xxx." example:="" t="" (df)="3.51," p=".001." d="0.65" df="degrees" of="" freedom="" note:="" partial="" eta-squared="" (partial="" η2)="" is="" a="" way="" to="" measure="" the="" effect="" size="" of="" different="" variables="" in="" anova.="" suggested="" norms="" for="" partial="" eta-squared:="" small="0.01;" medium="0.06;" large="0.14." results="" (related="" to="" hypothesis="" 1)="" •="" there="" was="" a="" significant="" main="" effect="" of="" gender="" of="" victim="" on="" severity="" of="" sexual="" harassment,="" f="" (df="" gender_v,="" df="" error)="____," p="___," partial="" η2="___." scenarios="" with="" male="" perpetrators="" and="" female="" victims="" (mpfv:="" m="___," sd=".___)" were="" perceived="" as="" more="" severely="" harassing="" than="" similar="" scenarios="" with="" male="" perpetrators="" and="" male="" victims="" (mpmv:="" m="___," sd="____)(see" table="" 1).="" (note:="" see="" slide="" 15="" for="" the="" corresponding="" means="" and="" standard="" deviations.="" use="" means="" and="" standard="" deviations="" for="" total="" male="" and="" female="" victims)="" results="" (related="" to="" hypothesis="" 2)="" •="" write="" the="" results="" related="" to="" hypothesis="" 2="" according="" to="" statistical="" data="" given="" above="" (note:="" see="" slide="" 15="" for="" the="" corresponding="" means="" and="" standard="" deviations.="" use="" means="" and="" standard="" deviations="" for="" total="" male="" and="" female="" participants)="" results="" (related="" to="" hypothesis="" 2)="" •="" there="" was="" a="" significant="" main="" effect="" of="" gender="" of="" participants="" on="" severity="" of="" sexual="" harassment,="" f="" (df=""> .05 was adopted to conclude statistical significance for the results results summary mean (standard deviation) the first independent variable “gender of victim” depicted in the test scenarios (within-subjects) female male the second independent variable “gender of participant” who responded to the test scenarios (between-subjects) female m=6.08 sd=(.79) 5.98 (.87) 6.03 (.80) male 5.83 (1.06) 5.73 (1.11) 5.78 (1.06) 5.97 (.93) 5.87 (.99) results report statistics in text: f ratio f (df-between, df-within) = xxx, p = xxx, partial η 2 = xxx example: f (2, 177) = 6.39, p = ,002, partial η2 = .07 t value t (df) = xxx, p = xxx. example: t (df) = 3.51, p = .001. d = 0.65 df = degrees of freedom note: partial eta-squared (partial η2) is a way to measure the effect size of different variables in anova. suggested norms for partial eta-squared: small = 0.01; medium = 0.06; large = 0.14. results (related to hypothesis 1) • there was a significant main effect of gender of victim on severity of sexual harassment, f (df gender_v, df error) =____, p=___, partial η2 =___. scenarios with male perpetrators and female victims (mpfv: m =___, sd = .___) were perceived as more severely harassing than similar scenarios with male perpetrators and male victims (mpmv: m = ___, sd = ____)(see table 1). (note: see slide 15 for the corresponding means and standard deviations. use means and standard deviations for total male and female victims) results (related to hypothesis 2) • write the results related to hypothesis 2 according to statistical data given above (note: see slide 15 for the corresponding means and standard deviations. use means and standard deviations for total male and female participants) results (related to hypothesis 2) • there was a significant main effect of gender of participants on severity of sexual harassment, f (df gender_p,df>