Gender Identity - Science topic
Gender Identity is a person's concept of self as being male and masculine or female and feminine, or ambivalent, based in part on physical characteristics, parental responses, and psychological and social pressures. It is the internal experience of gender role.
Questions related to Gender Identity
As a scholar, I am often faced with the question of whether a care provider (psychologist, therapist, counselor, or other professional) may or may not disclose their own sexual or gender identity when they provide care services to their sexually- and gender-diverse clients. I have so far not been able to find good resources on the topic, esp. those related to questions of whether professional identity may or may not be relevant in context of care; in cases if a decision is based on some individual circumstances, which those may be; or generally if there is some good peer-reviewed literature about this topic.
I'll end my question with a famous and not entirely unrelated line by Celia Kitzinger and their colleagues from 1998: "'Gay and lesbian sychologist'” can be heterosexual, just as a “social psychologist” can be anti-social or a “sports psychologist” a couch potato'" (Kitzinger et al., 1998, p532).
Thank you for your insights and time,
I have been looking at family violence data in Australia and noticed a pattern of gender symmetry emerging in DFV murder victimisation. While men are still over represented in DFV perpetration data, it has made me question why there is such a strong focus on segmenting data by gender in DFV research, and why there is such a high level of polarisation around discussions of DFV data and public policy.
During the match that took place between YouTubers around the world, there were only male members playing on the field. However, there are many female YouTubers who have a large number of followers. What is the reason that this only happened to a certain gender and did not happen to the other gender?
this is a comparative study question between Islamic law and Common law/ Civil law
Hello everyone, does anyone know how to calculate the simple size for a 2(gender: male, female)*2(culture: Asian, European)*2(age: children, adult)*2(direction: back, front)*2(position: left, right)*2( condition: confort, non-comfort) repeated ANOVA? We have 6 factors, among these, gender and culture are between-factors, while age, direction, position, and condition are within-factors. I'd appreciate it if someone can help me.
California Senator Scott Welk on Friday called on parents who "love their children" to flee the state before it's too late, in response to "disturbing language" in the "gender identification" bill.
The warning came after amending the "Gender Confirmation" bill among children's needs for "health, safety and well-being," according to "Fox News" channel. If parents refuse to confirm their child's preferred gender, they may face charges of child abuse and lose custody disputes.
Hi, I have data that are not distributed normally, i tried to make it normal by using log, inverse, or root square transformations but without any success. Are there non-parametric tests that can test moderation? So far i just analyzed men and women separately using Mann Whitney test (with the split file function in SPSS). Is there some way to explore whether the interaction with gender is significant?
To clarify gender mainstreaming and make women an essential and indispensable dimension in the process of designing, implementing, monitoring and evaluating policies and programs in the political, economic and social fields, so that women enjoy rights and freedoms on an equal basis with men, and so that the ultimate goal is achieved, which is the achievement of gender equality.
What are the biological differences between Sex and Gender?
How can we classify animals according to Sex and Gender?
How can teachers in schools in some countries explain Gender and sex for children? is that brainwashing or not? Can we teach children anything out of their awareness?
I am happy to share your ideas.
I am curious to know if is there any recent evidence suggesting that gender can play a role in the development of dissociative identity disorder, as well as the type and manifestation of the DID?
SOCIOLOGY AND HUMOR
Humor “breaks the ice” between strangers, and unites people in different hierarchical positions. It creates a sense of “shared conspiracy” as when gossiping or joking about superiors. The flip side is that those who do not join in the laughter, either because they don’t catch on, or because the joke targets them, will feel left out, shamed, or ridiculed. Joking relationships build group identity and solidarity. They promote communities over hierarchies and reveal ambiguities that enhance and subvert the expectations of people in religious and civic groups.
Laughter always ties into the humor of a particular social group—even if you are laughing by yourself at something you receive over the Internet. Some scholars argue that humor is a social corrective, linked with embarrassment. People learn what not to do when they see who gets laughed at. This goes back to the beliefs of Henri Bergson, who called humor a “social corrective…intended to humiliate.”
In the early 1980’s Emily Toth, wrote about the first “Humane Humor Rule,” “Never target a quality that a person can’t change.” Later Humane Humor Rules Include:
• Target yourself, i.e. use self-deprecating humor.
• Target your own ethnic group or gender, but no other ethnic group or gender.
• Never target the victim.
• Always target a strength so that it empowers rather than humiliates the target.
• Be sure that there is spatial, temporal and psychological distance before making fun of a tragedy.
• Remember: Tragedy + Time = Comedy
I want to compare customer groups by gender (Male and Female) for 'Willingness to Pay for Health Products.' However, 'Willingness to Pay for Health Products' is a latent factor measured by 3 observed variables. I am unsure how to compare them and have researched 'Levene's Test for Equality of Variances,' but I couldn't find how to run it in Stata. I'm in need of assistance!
I am trying to perfom a sample size calculation for neuroimaging study. Specifically, the participants, after filling questionnaire yileding a spefic score, perform a task in three different conditons, based on two different sensorial modalities and I have to study response accuracy between Male vs Female.
I would like just make sure that, beside the power and alpha level, I have chosen the paramters properly:
1) The effect size is a squared conversion to f Coehn from the Pearson correlation score;
2) 12 is the factorial product between 3 conditions X 2 kind of stimuli X gender;
3) Number of Predictors, 3 (referred to conditions, stimuli and gender);
4) Response variable, 3 (referred to accuracy in the three conditions);
Is this sample size analysis calculation well done?
The liberal view of gender ethics in the postmodern era, despite the demise of most major narratives, differs from the Islamic view or the view of anti-genderists,For reasons that seem logical to each of them, it is not permissible to resist or challenge them What led toThis endless debate lost the rights of many people, women and men alike
I am seeking to make an inventory and evaluate storybooks or projects that are intended to introduce concepts of gender equality or feminism to young children in the Sub-Saharan region or the Islands of the Eastern part of the Indian Ocean within the last 10-15 years.
As in French le/la, in German der/die/das & other languages, thera are genders for words & so articles in some languages. Grammaticaly gender for words are complete redundancy !? Governments have to cancel them offically as soon as possible so that people can learn those languages easily also. One of the reason English almost became universal language is due to being genderless for words !
"It's an inheritance from our distant past. Researchers believe that Proto-Indo-European had two genders: animate and inanimate. It can also, in some cases, make it easier to use pronouns clearly when you're talking about multiple objects."
As Mark Twain once wrote in reference to German:
“A person’s mouth, neck, bosom, elbows, fingers, nails, feet, and body are of the male sex, and his head is male or neuter according to the word selected to signify it, and not according to the sex of the individual who wears it! A person’s nose, lips, shoulders, breast, hands, and toes are of the female sex; and his hair, ears, eyes, chin, legs, knees, heart, and conscience haven’t any sex at all…”
I am definitely not an expert in statistics, so I was wondering if someone could assist me in selecting the appropriate (and simplest) statistical test.
My research focuses on examining the impact/relationship between weight and shape concerns (ratio variable) on excessive exercise (ratio variable) while considering two moderators: anxiety (nominal, dichotomous) and gender (nominal, dichotomous).
Which analyses would you recommend? Additionally, would you include both moderators in the same model or would you conduct separate analyses?
Thank you in advance for your help.
To Whom It May Concern
Kindly, if anybody there is interested in collaborating with me as well as other psychology researchers on the topic of personality, please let us know. Right now we are investigating "Narcissistic Personality Traits" in correlation to age, gender, perception, causal attribution, culture, PNI dimensions, etc.
Please, if interested send me/ us a CV to:
I'm looking for a database with data on several corporate governance structures such as;
Board Size, Board Independency, CEO Duality, Board Gender Diversity, etc.
Is there a database around that holds this kind of data for e.g. NASDAQ or NYSE companies?
Furthermore, I am looking for a database that contains data with information from annual reports such as Audit Commitee Size or Number of Board Meetings.
Instead of collecting this data by hand out of firms' annual reports, it's more efficient if there is a database available that contains this kind of data. Is there any?
I am reading about Refinitiv, BoardEX or Bloomberg. Somebody who can help me out?
Thanks in advance.
Firth logistic regression is a special version of usual logistic regression which handles separation or quasi-separation issues. To understand the Firth logistic regression, we have to go one step back.
What is logistic regression?
Logistic regression is a statistical technique used to model the relationship between a categorical outcome/predicted variable, y(usually, binary - yes/no, 1/0) and one or more independent/predictor or x variables.
What is maximum likelihood estimation?
Maximum likelihood estimation is a statistical technique to find the best representative model that represents the relationship between the outcome and the independent/predictor variables of the underlying data (your dataset). The estimation process calculates the probability of different models to represent the dataset and then selects the model that maximizes this probability.
What is separation?
Separation means empty bucket for a side! Suppose, you are trying to predict meeting physical activity recommendations (outcome - 1/yes and 0/no) and you have three independent or predictor variables like gender (male/female), socio-economic condition (rich/poor), and incentive for physical activity (yes/no). Suppose, you have a combination, gender = male, socio-economic condition = rich, incentive for physical activity = no, which always predict not meeting physical activity recommendation (outcome - 0/no). This is an example of complete separation.
What is quasi-separation?
Reconsider the above example. We have 50 adolescents for the combination- gender = male, socio-economic condition = rich, incentive for physical activity = no. For 49/48 (not exactly 50, near about 50) of them, outcome is "not meeting physical activity recommendation" (outcome - 0/no). This is the instance of quasi-separation.
How separation or quasi-separation may impact your night sleep?
When separation or quasi-separation is present in your data, the traditional logistic regression will keep increasing the co-efficient of predictors/independent variables to infinite level (to be honest, not infinite, the wording should be without limit) to establish the bucket theory - one of the outcomes is completely or nearly empty. When the anomaly happens, it is actually suggesting that the traditional logistic regression model is outdated here.
There is a bookish name of the issue - convergence issue. But how to know convergence issues have occurred with the model?
- Very large co-efficient estimates. The estimates could be near infinite too!
- Along with large co-efficient estimates, you may see large standard errors too!
- It may also happen that logistic regression tried several times (known as iterations) but failed to get the best model or in bookish language, failed to converge.
What to do if such convergence issues have occurred?
Forget all the hard works you have done so far! You have to start your new journey with an alternative logistic regression, which is known as Firth logistic regression. But what Firth logistic regression actually does? Without using much technical terms, Firth logistic regression actually leads to more reliable co-efficients, which helps to choose best representative model for your data ultimately.
How to conduct Firth logistic regression?
First install the package "logistf" and load it in your R-environment.
Now, assume you have a dataset "physical_activity" with a binary outcome variable "meeting physical activity recommendation" and three predictor/independent variables: gender (male/female), socio-economic condition (rich/poor), and incentive for physical activity (yes/no).
pa_model <- logistf(meet_PA ~ gender + sec + incentive, data = physical_activity)
Now, display the result.
You got log odds. Now, we have to convert it into odds.
odds_ratios_pa <- exp(coef(pa_model))
Game over! Now, how to explain the result?
Don't worry! There is nothing special. The explanation of Firth logistic regression's result is same as traditional logistic regression model. However, if you are struggling with the explanation, let me know in the comment. I will try my best to reduce your stress!
Note: If you find any serious methodological issue here, my inbox is open!
The title of my study is 'The sociocultural factors that influence body image and self esteem of young people'. The sociocultural factors I am looking at are media, and friends and family. My aim is to see which of these factors has the greatest impact on body image and self esteem, and to see whether males or females are more influenced by these factors.
My DVs are body image and self-esteem, and my IVs are media, friends and family, and gender. Any help would be really appreciated !
where as gender is socially constructed concept to refer the role of men and women in society, the term is also used to replace sex by many people. if so, how can we determine whether they are used to refer to one idea or the other?
I am looking for recent quantitative studies on gender and ethnicity discrimination in higher education in English, French or German. Thank you.
I was wondering whether there are any texts on the experiences of Romanian scholars in gender and queer studies vis-a-vis the governmental attempts at banning "gender theory" in higher education. Anything would help - academic texts or other media.
Gender relations in the Mediterranean region are a kaleidoscope of overlapping social, economic and cultural roles, spread across a diverse multitude of countries and communities. The European Mediterranean countries have distinct social patterns and gender norms, which differ from the MENA Mediterranean countries, for example. Additionally, the political climate in the region also determines how women and men are able to access and leverage sustainable development opportunities to be able to cope with climate risks, and achieve social and environmental co-benefits.
The degree to which people are affected by climate change impacts is partly a function of their social status, gender, poverty, power and access to and control over resources. Despite the international community’s increasing acknowledgement of the differential experiences and skills women and men bring to development and environmental sustainability efforts, women still have lesser economic, political and legal clout and are hence less able to cope with—and are more exposed to—the adverse effects of the changing climate.
Detrimental effects of climate change can be felt in the short-term through natural hazards, such as landslides, floods and hurricanes; and in the long-term, through more gradual degradation of the environment. The adverse effects of these events are already felt in many areas, including in relation to, inter alia, agriculture and food security; biodiversity and ecosystems; water resources; human health; human settlements and migration patterns; and energy, transport and industry.
In many of these contexts, women are more vulnerable to the effects of climate change than men—primarily as they constitute the majority of the world’s poor and are more dependent for their livelihood on natural resources that are threatened by climate change. Furthermore, they face social, economic and political barriers that limit their coping capacity.
I have the following doubt:
Can a model be proposed if it is tested through two or more different tests?
The model is figured how A influencing C, with a mediation from B. Gender is considered as moderator on all effects.
However, it is tested through different regressions run with process:
(1) A, gender, interaction AxGender -> B
(2) A, B, gender, and the interactions AxGender, BxGender -> C
I have my opinion, but I would like to hear other researchers first. What is your opinion in this regards?
Hello, I'm currently working on my data analysis but I'm not sure what statistical test to use.
My research objective is: To determine the effect of age, gender, and GPA on the work readiness of graduating students
My hypotheses are:
- H1: Age significantly affects students' work readiness
- H2: Gender significantly affects students' work readiness
- H3: GPA significantly affects students' work readiness
In my study, work readiness is measured through a Likert-scale instrument (from 1 to 5), and I'll derive the mean scores to interpret work readiness.
Senior Leaders in higher ed have the power to make and execute changes. Yet, data show that the leaders’ gender, race/ethnicity (Johnson, 2021), inexperience in leadership style, and their predecessors' policies and informal groups (Fagan et al., 2022; Guo et al., 2020; Javeed et al., 2019; Marchiondo et al., 2021) can impact their power/influence in the making decisions or implementing anti-racist policies. This influence continues to adversely affect the Black, Indigenous, People of Color (BIPOC) geoscientists on campuses and neighboring communities (Wolfe & Riggs, 2017).
What else am I missing?
Guo, Y., Zhu, Y., & Zhang, L. (2020). Inclusive leadership, leader identification and employee voice behavior: The moderating role of power distance. Current Psychology, 41, 1301-1310.
Javed, B., Abdullah, I., Zaffar, M., Haque, A., & Rubab, U. (2019). Inclusive leadership and innovative work behavior: The role of psychological empowerment. Journal of Management & Organization, 25(4), 554-571.
Johnson, G. (2021). Gender, diversity, and the United States judiciary. SAIS Review of International Affairs, 41(1), 61-71.
Marchiondo, L. A., Verney, S. P., & Venner, K. L. (2021). Academic leaders' diversity attitudes: Their role in predicting faculty support for institutional diversity. Journal of Diversity in Higher Education, 1-10.
Wolfe, B. A., & Riggs, E. M. (2017). Macrosystem analysis of programs and strategies to increase underrepresented populations in the geosciences. Journal of Geoscience Education, 65, 577-593.
There are two categorical data i. e., gender and color preference like red, yellow and green which has no specific order value.
In this data, we want to know that how the gender associated with color preference and also there are more demography variables which also affect the color preference. How can we measure the predictor?
Dear Researchgate Community,
I need your suggestions for methods that can be adopted for gender inclusion assessment at different levels. The focus of this topic shall remain on social life and community development.
Specifically, I'll be interviewing people in a community where the idea of fluid gender is likely scoffed at by most people. However, I still need to know their self-identified genders, so I have to find a way to ask without also distancing myself from them through the very act of asking. For instance, a participant might not only not believe in gender fluidity but also be insulted that I would even ask because that would imply that I can't tell if they consider themselves to be a woman or a man or something else. For those with experience in this sort of environment, how do you ask the question?
Education discrimination could occur based on ethnicity, nationality, age, gender, race, economic condition, disability and religion. The germane question is" how can we pragmatically combat discrimination and prejudice in schools?" Sharing is caring. Thanks
thank you for reading my quistion and i will appreciate any help. i am doing my master dissertation now which i am investigating gender represenatation in textbooks. my method is content analysis and i will collect data which includes genders of poets, scientists, authours, leaders and so on. i also will look at the appearance of each genders in varied areas. the data will be gathered from texts and pictures and i will interpret it (after analising) in charts and diagrams.
my quistion is does this process considered as qualitative or quantitave or mixed methods? and about the data is it qualitative data or quantitative ?
I am currently running a Multiple Linear Regression with 4 independent and one dependent variable. My moderator is gender (0=female, 1=male). Now I would like to investigate whether there are gender differences in the influence of gender on the independent variables.
And now the question arises whether I can split the data in SPSS according to female and male and then see whether the respective independent variables are significant for women and men and then use the non-standardized coefficient B to compare for whom the effect is more pronounced is or do you have to do something different to investigate this moderation?
Thanks in advance!
I am attempting to explore the relationship between my recorded demographic data (age, gender, education, house income bracket, number of dependents and number of pets - all these are categorical) and the results of a wellbeing questionnaire (the results are displayed in a singular total score).
I am not sure how to proceed in exploring this relationship and examining an possible correlations or the most appropriate analysis within SPSS.
Any advice would be greatly appreciated.
I would like to do a multiple regression with 4 independent variables and 1 dependent variable. Also i have a dichotomous moderator "gender" which is split in female = 1 and male = 2.
How do i test the moderator with SPSS to see if it is linear?
I have already checked the assupmptions of the multiple linear regression with the dependent variables and independent variable using partial regression plots, But how can i check the dichotomous moderator if it is linear?
Thanks in advance!
I am looking for articles that could explain why new fathers are reporting less needs than mothers, probably due to gender communication or else.... if anybody has article who highlights the differences in needs between mother and father or men and women and why this difference exist.....
I would be very happy
When I embarked on this journey of exploring more on exploring the condition and status of gender equity and equality in architecture, or public spaces, or urban design, I found very little literature is available. Would be great to discuss on this topic. I have started to get an impression perhaps this topic is irrelevant or not trending at all. But I have strong feeling that has an importance, but very little research has been done on this. Would be great if you know of some documents or share some light on this.
After running hierarchical regression based on attachment and gender, both of my attachment scores (anxious and avoidant) have significant negative interactions with gender. I gender coded results as male=1 and female=2. How do I interpret this negative interaction?
I think this could mean that higher attachment scores are stronger predictors for males than females, but I'm not 100% sure that's right
Response variable: teachers` implementation of Differentiated instruction, their familiarity with, and use of, differentiated instructional strategies.
Predictor variable: gender, years of teaching experience, teaching grade level, teaching subject, teaching load, types of school they work in – primary, middle, and high school, and qualification.
Please answer my question.
If my dependent variable is open defecation and has one value (yes) and my independent variable is gender with two values (male and female). How do I go about it in spss if I intend to do a chi square test?
For example: I have this data - Gender (Male = 244, Female = 95) that practiced open defecation. I would like to test if there is an association between gender and open defecation practice. Thank you
Do you dummy cope gender within Pearson r correlation?
Do you dummy code gender within multiple hierarchial regression?
Do you have to dummy code gender even when your aims of your study are not looking at gender?
I am trying to assess factors affecting publication outcomes among Radiology residents such as Gender (male vs female residents) but there are 3x more males in my sample population.
Your replies will be helpful towards completion of MPhil research.
I got set of data that includes:
Gender: categorical (classified as IV in jasp)
Ethnicity: categorical (classified as IV in jasp)
Congruent: continuous data (classified as DV in jasp)
Incongruent: continuous data (classified as DV in jasp)
I have been asked the following questions:
Is there a significant interaction between ethnicity and implicit association?
I am struggling to choose the correct test; I am trying ANOVA but actually I don’t know what I should measure to answer the question!
Is it the interaction between Ethnicity and gender? What about congruency data?
I am looking at gender equality in sports media. I have collected two screen time measures from TV coverage of a sport event - one time for male athletes and one time for female athletes.
i am looking for a statistical test to give evidence that one gender is favoured. I assume I have to compare each genders time against the EXPECTED time given a 50/50 split (so male time + female time / 2), as this would be the time if no gender was favoured.
my first though was chi square? But I’m not sure that works because there’s really only one category. I am pregnant and so my brain is not working at the moment lol. I think the answer is really simple but I just can’t think of anything.
I'm doing my research entitled, "The Bystander's Attitude Towards A Person's Gender and Their Willingness to Help Them: A Correlational Study". I originally planned to use Pearson-r to determine if there is a significant relationship between the two variables, but my professor told me that Chi Square is more appropriate.
I was tasked to use SPSS process for my thesis and check if participant generation (Gen X, Millenial, and Gen Z) has a moderating effect on the regression between the IV and DV. How could this work? Every video I’ve seen so far seems to use just dichotomous categorical variables such as gender. Should I dummy code each generation as 1,0 like other videos suggested or is there another way to use a non-dichotomous variable?
Hello, I have been working with gender issues in urban studies and I am looking for studies that have used photographic activities as a methodological tool with older women.
Thank you in advance!
I am conducting a study evaluating the effects of product X on their sleep patterns over time. There are 3-4 time points and drop outs at each time point. These are the same participants and my client wants to take gender, age, and dosage into consideration when examining effects. I thought of conducting a repeated measures ANOVA but the drop outs would not allow me to conduct an accurate test. Is the only option to eliminate the incomplete cases? Would an MMRM work?
Gender representation in numerous school textbooks across diverse societies has been studied and discussed since the 1970s. A substantial number of these studies stated that gender bias in textbooks (GBIT) is quite stubborn and practically a barrier in the way of gender inequality (Ullah & Haque, 2016). In particular, in textbooks of Social Studies, the construction of gender is solely stereotypical (Jabeen, Choudry, Omar, 2014). Hameed (2012) in his study on gendered based English textbooks found that in shaping up ideas of the children and for encouraging optimist gender roles in children, textbooks play a decisive role and can be a valuable tool. Further, Jabeen and Illyas (2012) emphasize that characters in (learning resources (textbooks) play a significant part in children. Characters influence children's choices concerning to what type of being they want to become (Jabeen & Illyas, 2012).
Unterhalter and North (2010) therefore argue that to achieve gender equality through education, the concerns of men and women would be considered as integral parts monitoring, designing, evaluating policies programs in all social, political, and socio-economical domains to provide equal benefit for men and women and to not perpetuate inequality. Emphasizing on efficiency approach of Gender and Development (GAD), Cornwall (2000) also mentioned that men as oppressors and women as a victim of gender inequalities is a simplification of reality. So, there is a need to view gender, not as a unilateral issue of women but it should also be considered in terms of power relations and powerlessness where men and women may be dis-empowered and vulnerable (as cited in Gender analysis framework of Leach, 2003, pp.10-11).
This article suggested weighted population density in some epidemiological studies.
Do you know in which type of study weighted is preferable? Should other population characteristics be weighted also? Such as gender ratio, population income... Also, some events, such as infectious disease and healthcare utilization, are strongly related to density.
Many thanks for considering my request.
The UK government defines gender as: "a social construction relating to behaviours and attributes based on labels of masculinity and femininity; gender identity is a personal, internal perception of oneself and so the gender category someone identifies with may not match the sex they were assigned at birth where an individual may see themselves as a man, a woman, as having no gender, or as having a non-binary gender – where people identify as somewhere on a spectrum between man and woman.
Based on the above mentioned concept, would it be reasonable to express gender not qualitatively, but quantitatively (e.g. as self-reported score reflecting how much 'masculine' or 'feminine' an individual is self-identified on a visual analogue scale)?
I have a base model: leader ~ gender + posture leader is the dependent variable. gender and posture independent variables.
I want to control for control variable, like probands' gender, age etc. To solve this, I use an Anova to compare the base model with complex model ( leader ~ gender + posture + probandGender ). If it's significant, the control variable probandGender will have a meaningful influence on the model, and thus it should be kept for further analysis. Is that correct so far?
If yes, it leads me to my actual question:
Variable gender has two categories (female and male), but it consists the pictures of 2 males (male1, male2) and 2 females (female1, female2). Hence, there is the control variable single_person. I want to control, if the gender effects is reliable, or a single person stands out and make it significant. Is it allowed put single_person into a term like leader ~ gender + posture + single_person and to compare it to the basic model like before? it feels wrong, because it's like single_person is in gender. Are they nested?
Thank you for any idea.
Persoalan sosial yang disebabkan isu gender senantiasa mengemuka, bagaimana pandangan anda berkaitan hal isu gender dengan konsepsi manusia dan kebudayaan?
Silakan dijawab dengan Bahasa Indonesia ataupun Bahasa Inggris. Terimakasih.
My group is conducting a study to determine if our 3 IVs are predictive of the DV, and which among these IVs is the most significant predictor, thus the use of forward selection. However, before that, we would like to control for two of the other variables which are gender (male, female) and academic track (HUMSS, STEM, ABM). I'm aware that to control for these variables they must be first entered into the regression before commencing forward selection. If gender only was to be controlled, I would have no trouble. But with the presence of the other categorical variable academic track, I have found myself confused in the process. Hopefully someone can help me figure this out.
I used AMOS to test the moderating effects of demographic variables (gender, age, marital status, education, and income). However, the results of multiple group analysis and interaction moderation are largely different. (n=302)
In particular, when using MGA for testing moderating effect, marital status significantly moderates the effect of the independent variable on the dependent variable,
Estimate P Estimate P z-score
ITUT99 <--- EFCT99 0.335 0.001 -0.033 0.686 -2.802***
ITUT99 <--- PFCT99 0.261 0.008 0.656 0.000 2.894***
but when using the interaction method, these interaction effects are non-significant. (I standardized values of the independent variables and demographic variables, interaction = Zindependent*Zmaritalstatus)
Estimate S.E. C.R. P
ITUT99 <--- PROxMAR .221 .205 1.076 .282
ITUT99 <--- EMOxMAR -.208 .206 -1.012 .312
I am very grateful if you can help me explain why there is a big difference in results between the two methods. Are there any ways to improve the results in the interaction effect?
I am looking for a gender stereotype scale to test leader gender stereotypes. Any recommendations would be appreciated.
I study how gender can moderate the relation between driving self-efficacy and the tendency to get distracted while driving. I found a non significant self-efficacy*gender interaction effect (p=.19). However when I looked at the plot I found this (attached file).