Science topic

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.
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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?
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Thank You so much Sir
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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.
Thanks
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Guidelines for the assessment of gender mainstreaming (fao.org)
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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?
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Again, if it is relevant to the research objective or question to investigate, ask it . My very simple point is that it is the decision of the researcher what to ask, this is called academic freedom. If her / his research result is rejected by reviewers such as you, so be it. That's the price of free thought and inquiry. You insist in educating me, and I thank you for your dedicated effort. I do understand sampling and populations, as you do also. But what if I'm not interested in the population and simply in the subjects being studied? Do you think King Tut was representative of the ancient Egyptian people? Yet whole volumes have been written on this person. Not all research is alike, not all of us are ignorant, we simply choose what to investigate and how to conduct our research. This issue of what to ask is the absolute right of the researcher. Professional societies, journals, as well as disciplines can have guidelines, not royal decrees on what to ask. I still think that the healthiest adjective for this discussion is a difference of opinion. The alternative means that I do not have the right to think the way I do. That's what they told Galileo in 1633... although I'm certainly not Galileo!
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I'm looking for a database with images of gender-neutral faces for a study I'm looking to propose for class. Thanks for the help!
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Hi Maddy, did you find such a dataset? I'm also looking for it
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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
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hello ..
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 ?
thank you
Fatema
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Mixed methods requires two sets of results, one qualitative and one quantitative, as well as the integration of the those sets of results. A straightforward content analysis such as you propose would not meet this definition.
Instead, it sounds like you want to do a quantitative content analysis (i.e., based on counting things), but you want this analysis to be essentially descriptive (i.e., you will not be testing any hypotheses).
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Answers are no more needed
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Yes. A problem with using the exact ages in a correlational analysis is the split between the two age groups, so you don't have a continuous distribution of age. A Fisher exact test might be best given the small sample size. I agree that the analysis might be rather sparse, but that is a limitation of your data. For publication, I suggest that you aim for brief report rather than a full article.
You would report the 2-tailed p-value if you had no a priori hypotheses and your experiment was exploratory, but a 1-tailed if you predicted a specific result. SPSS can do a Fisher exact, but how you access that depends on the version you are using. It's rather tedious to do a Fisher exact by hand IMO.
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Hello,
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!
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No, it seems that you did not understand the fundamentals of moderation analysis, I suggest to read an introductory book on regression (like Cohen, Cohen, West & Aiken as the seminal classic). Your approach is wrong, since it does not test the research question. The regression coefficients test, if the coefficient is significantly different from zero (so in the split case, each coefficient would be tested against zero idependently). But moderation is concerned with the question if these two coefficients differ from each other, which cannot be derived from each individual coefficient itself. It may be the case that there is an significant effect for man and an sig. effect for women, each, but that this two coefficients differ from each other, because the effect is more pronounced in one of the groups. Do you know what I mean?
Therefore, you need to learn the principles of multiple regression and/or consult a local statistician, to help you, because there may be some pitfalls you cannot identify without a decent understanding of the topic.
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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.
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With the obvious exception of gender, your independent variables are either linear or can be converted into linear formats. In particular, number of dependents and number of pets are already acceptable for regression analysis. For education, you can code this in years for the mid-point of each of your categories, and the same for income. (And gender can be coded as a 0-1 dummy variable in the analysis.)
These are all standard produces for working with this kind of data.
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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.
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Thank you.
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Hello everyone,
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!
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Again, there is no way that a dichotomous variable could have a non-linear relationship with another variable. Therefore, no need or possibility to check for non-linearity.
You can see this by plotting the dichotomous variable against the DV in a scatter plot. The dichotomous variable has only two possible values on the x axis. The OLS regression line will go through the group means. You could not fit anything other than a straight line through the two means.
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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
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Visit also the following useful RG link:
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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.
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Designing Gender Sensitive Public Spaces – Cidco Smartcity (niua.org)
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Your replies will be helpful towards completion of MPhil research.
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Thanks.
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Gender in Agricultural development
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Gender issues are common in agriculture all over the world, mostly in developing nations.Women do most of the agricultural work and they are still paid less as compared to male for the same level of work. Particularly for maize,in my view knowledge level of both male and female in production may be the issue.
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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
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Hello Kirsty,
can you 1) repeat the analysis with gender dummy coded (0/1) and 2) present the complete regression table (please don't post it in the text field but attach it as a text file).
All the best,
Holger
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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.
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The order of entry of variables in a hierarchical regression depends on your hypotheses. It is a question of theory, and so it is not determined by any statistical issues.
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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
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Before being able to answer your question, I think you should address one key point. You stated that "my dependent variable is open defecation and has one value (yes)". I suppose that all the other answers were left blank. The issue here is that a blank answer may either stands for a "no" or a "I don't want to answer". Consequently, it would be hardly possible to assess whether there could be an association between gender and open defecation practice. At most, it would test for whether there is an association between gender and the willingness to answer to this kind of questions.
Accordingly, if you choose to use a 2x1 design you should opt for a non-parametric test. Otherwise, you might recode blanks into "no/I don't want to answer" and compute a Chi-Squared.
Finally, since Chi-Squared tests are sentitive to sample size, you may want to evaluate the effect size of your test.
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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?
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that should read ratio data, not ration data.
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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.
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Thank you very much!
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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?
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Chi square test for association of categorical variables.
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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.
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independent sample t-test best
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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.
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In a simplistic way. Chi square is used when you want to establish an association relationship between two qualitative variables. Meanwhile, pearson is used when you want to establish a relationship between two dichotomous quantitative variables.
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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?
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I agree with both answers by Christian Geiser and Bruce Weaver , but if you really need/want to use PROCESS (which is not necessary as explained), there is a button "multicategorical" since at least version 3.5 (I did not check for even older versions), where you can tell PROCESS which variables (including moderators) are multicategorical and also which coding scheme should be used (e.g. indicator, effect...).
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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!
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Hi Thais,
I'm fascinated by your research as I am also considering to do digital/ photography ethnography for my future research on women's entrepreneurship in poverty contexts. Have you read Sarah Pink and colleague's work on digital ethbography? You may find some inspirations there.
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Hello everyone,
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?
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I'd use a mixed model before considering imputation.
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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).
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There is need to relook at the true meaning of gender-neutral laws on sexual harassment which should aim at protecting both men and women against sexual harassment in work settings. An enabling environment for prompt reporting and quick redressal with an unbiased investigation and a well laid out counselling system to ensure safety, as well as emotional and mental support to the victims, are important preventive strategies. These measures may help address the problem of hesitancy &/or other reasons for non-reporting. It is also pertinent to offer the accused a fair opportunity to defend, as there may be instances of false allegations
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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.
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Suraj Kapoor , thanks Mr Kapoor. It is very interesting paper. However, they only say: "that is better sutied" without explanation, but providing great practical examples.
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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)?
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Vasileios Papadopoulos If I understood you correctly, you have research in mind in which you would like to correlate gender with other variables. Maybe you could use two continuous variables? One with the poles of "gender identity existing - no gender identity" and the other one with "masculine - feminine".
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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.
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، وبالتالي يجب الاحتفاظ به لمزيد من التحليل.
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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.
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Selamat sore, Pak.Izin memberikan pandangan mengenai suatu permasalahan yang berkaitan dengan gender dan budaya yang sudah sering kita dengar, Ditambah lagi di Indonesia kita memiliki budaya yang amat beragam.Menurut saya permasalahan terkait hal tersebut datang dari faktor internal dan eksternal.
Faktor internal contohnya doktrin pemikiran dari keluarga,kerabat,dll. Sedangkan faktor eksternal doktrin pemikiran dari bangsa luar melihat gender maupun budaya.Yang sering menjadi permasalahan yaitu adanya pemaksaan kehendak dari seseorang dari doktrin internal dengan seseorang yang mendapat doktrin dari bangsa luar atau modern.
Contoh yang dapat kita ambil yaitu isu adanya kesempatan wanita dalam memilih ingin memiliki anak atau tidak memiliki anak. Hal ini pasti menyebabkan banyaknya pendapat antar individu. Oleh karena itu, untuk mencegah permasalahan yang bersumber dari gender dan budaya ini adalah memahami bahwa memang kita memiliki perbedaan pendapat maupun budaya sehingga dari sikap tersebut tumbuh toleransi yang mendahulukan kepentingan bersama daripada kepentingan pribadi saja.
Hal yang ingin saya tekankan toleransi yang dimaksud bukan berarti membenarkan segala pemikiran-pemikiran baru yang dibawa oleh bangsa luar.Pada dasarnya kita tau itu adalah hal yang salah dalam nilai-nilai kehidupan berkebangsaan namun kita membenarkannya karena kata toleransi tersebut, contohnya LGBT.
Mohon arahan dan bimbingannya selalu, Pak. Siap terima kasih, Pak.
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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.
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I usually agree with James and David on statistical issues but here I do not. If you want the most accurate prediction equation I have to suggest adaptive lasso because of it's oracle properties. I'm going to suggest that you use R as your stat package if you're not familiar with R I recommend an excellent book. You will find how to download it from the z-library. This includes how to download everything for free. That is is the first attachment. The second attachment includes a full description of why you should use adaptive lasso and included in the references are the complete details. Third attachment contains R code to run all of this. Cut and paste it into a text file and you are ready to go. If you have questions please feel free to ask. Best wishes David Booth
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Hi peers,
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,
Single Married
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?
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Hoang T.P.M. Le Engagement is more general than moderation. The function of the two variables involved in the interaction is distinguished by moderation. So, when we state X and Z interact in their impacts on an outcome variable Y, there is no actual differentiation between X's and Z's roles.
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How is your view?
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Many Chinese citizens are skeptical about the state’s renewed effort to control childbearing. Online discussions are ripe with worries about the new policy’s effects on employment and families and how unfair population policies are for women. Many women worry about being pushed out of the labour market and losing the right to equal work opportunities with relaxed birth quotas. There is very real concern that discrimination against Chinese women will only worsen with a three-child policy.
Openly discriminatory hiring requirements leave working women at a disadvantage. Despite being illegal, many job ads list a distinct requirement for men or married women with kids, and other employers convey such a preference during the hiring process. In 2020, 11 percent of postings on the Chinese government’s national civil service job list specified a preference or requirement for men. The preference for married women with kids also disadvantages single women and those with no or fewer children. Under the three-child policy, women with two kids can now legally have another, making them “risky” hires in employers’ eyes and, thus, prone to discrimination.
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Ethnic, gender, or generational diversity?
As awareness of corporate sustainability grows and organizations around the world adopt ESG, what is harder to achieve in top management? Ethnic, gender, or generational diversity?
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I believe the most difficult to achieve in top management is generational diversity. Strategies for working on corporate sustainability that involve everyone with their beliefs, ways, cultural heritage, etc. are not simple to develop. Breaking some paradigms becomes a barrier to the adoption of ESG.
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Hello,
I am looking for a gender stereotype scale to test leader gender stereotypes. Any recommendations would be appreciated.
Thank you!
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Hi
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).
I don't know what to do with this... Can you help?
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I would look into the role of the covariates - Is the interaction significant when they are removed from the analysis? If the interaction in the "clean" model (i.e., without covariates) is still insignificant, then I would be extremely cautious of its viability. If it is significant, maybe you can check whether your research question necessitates controlling for the covariates you included in your analysis.
Good Luck!
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when analyzing a likert scale of attitudes of people containing items concerning the attitudes related question , can it's hypothesis be form with the statement of item which is being taken as dependent variable? such as there is a relationship between gender and perception of people (infidelity is an unacceptable behaviour) .What is the correct way of writing a meaningful hypothesis in such case?
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You can use any reasonable source for an idea that you develop into a hypothesis. However, items in a "Likert scale" are assumed to be different ways of tapping the same basic construct. Just because items are scored in the Likert format doesn't mean that they add up to a scale. If an item in a scale (Likert-format or not, it doesn't matter) gives you an idea for measuring a different construct, then of course you can use that idea to devise a way to measure that construct, which could then be tested with regard to its predictors or correlates. David L Morgan has given some suggestions.
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I am studying the lived experiences of Black high school seniors and college students concerning their perception of race and gender issues in the school environment, and how they were able to overcome adversity related to issues of race and gender.
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Both the methods ( case study or counter narrative) can be applicable. But may be counter narrative will be more suitable as these arise from the vantage point of those who have been historically marginalized.
You may refer to these articles also:
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Is it possible to run a correlation test on a continuous DV and a categorical IV with 3 levels?
I'm investigating is gender is associated with academic procrastination, however, my gender variable is coded as: 0 = Male; 1 = Female; 2 = Non-Binary.
Initially I ran a Pearson product-moment correlation coefficient test however, I have now realised that this may not be the right procedure.
Any help would be greatly appreciated!
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Run ANoVA test with tukey HSD
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I need help with narrowing on a topic for my Masters dissertation in International business and the area I am interested in is women/ gender in business. Please anyone with good topics in this area can assist.
Thanks
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I am doing moderated mediation analysis using Process Hayes (model 58). The moderating variable is gender - male / female. Do I have to centralize the gender variable by encoding 1; -1 before analyzing in Process?
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Standardization shouldn't significantly impact your results but I would recode the gender variables to be positive numbers (i.e. 0, 1, 2) for your reader's clarity.
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I would really appreciate your help on this. I have tried a load of things and I haven't yet found the one that works.
I am using the Bem Sex Role Inventory in my dissertation, which involves classifying people as masculine, feminine, androgynous and undifferentiated, based on their score on two different scales: a masculine one and a feminine one. Classification depends on whether they score at or above the mean, or below it, on the two scales. I have created separate variables for masculine and feminine, using 1 and 0 to denote whether they scored above or below the mean. The new variable I am trying to calculate needs to reflect the following:
0-0= undifferentiated (new variable = 4)
1-1= androgynous (new variable=3)
M0-F1= feminine (new variable=2)
M1-F0= masculine (new variable=1)
I have run the following syntax, and tried doing the same through Compute Variable, but I end up with all missing values. Please tell me what I'm doing wrong!
COMPUTE BSRI_CLASS=0.
IF ((BSRI_M_CLASS= 1) & (BSRI_F_CLASS = 0)) BSRI_CLASS=1.
IF ((BSRI_M_CLASS = 0) & (BSRI_F_CLASS = 1)) BSRI_CLASS=2.
IF ((BSRI_M_CLASS = 1) & (BSRI_F_CLASS = 1)) BSRI_CLASS=3.
IF ((BSRI_M_CLASS = 0) & (BSRI_F_CLASS = 0)) BSRI_CLASS=4.
Thank you in advance.
Laura
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Hi Mikaella, it’s a while ago now, but I’m happy to try to help if you tell me a bit more about what the issue is. From memory, in the end my problem was solved by having a really good think about it, and using Compute Variable, so that as much as possible was generated by SPSS itself, rather than me manually entering syntax- that’s how I eliminated whatever error I was making! Do write back if you‘d like to give me any more information. Best, Laura
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Hello my friends - I have a set of independent variables and the Likert scale was used on them and I have one dependent variable and the Likert scale was used as well. I made the analysis and I want to be sure that I'm doing this right - how I can use control variables such as age, gender, work experience and education level as control variables to measure their effect on the relationship between the independent variables and the dependent variable? Please give me one example. Thanks
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This link will be useful for you: Check:-
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Based on gender identity, learners might show different characteristics that might influence the SLA.
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Dear Ullah, what a fascinating research question with regard to how particular learner variables might affect L2 learning outcomes (although this specific variable cannot be changed by instruction itself)! I would be surprised if no one has looked into this question more systematically yet. I have frequently observed that gender differences are reported in the results sections of L2 learner studies "as a side observation", even if the research topic itself was not gender differences. I also happen to know that FLA is consistently higher among female students. Overall, I would expect L2 learning outcomes in students to be mediated by differences in other variables (FLA, motivation, grit, etc.) that show different non-overlapping distributions between genders.
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I am running a study to see how sexuality (I’m looking only at gay and heterosexual men- so a binary IV) and types of gender expression (masculine, feminine, androgynous, or undifferentiated- so a nominal IV) affect scores on a scale measuring symptoms of muscle dysmorphia (so a discrete possibly continuous DV).
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Katie Madeline Wyndzen, I want to thank you so much for the time you took to respond and provide some options to me and your insight on this inventory to help guide my next steps. Stats are tough for me so this was a huge help. I went with option two per your suggestion and agree that's a really good way to read the categories. Thank you!
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Excuse me if this is a question with an obvious answer (I am a MSC student not a professional researcher). I am exploring the the correlates between a number of variables (different social skills with anxiety, age and cognitive factors). I also wanted to see if there are gender differences between these variables/correlations.
Comparison of means between genders shows no significant difference between males and females for any variable.
If I enter gender as a variable and explore correlations with other variables there are also no significant correlations.
However, when I use the split-group function (by gender) on SPSS and run my correlation analysis for all other variables (not inc. gender)- some correlations are significant just for male participants and some for female. I just want to check that this makes sense (I think it does). I imagine that by using the split-group function this in some ways works a bit like using gender as a moderator? In that I can see how gender impacts the relationship between certain variables? (e.g x correlates with y but only in group a not group b). So I believe I have found that although there are no differences in mean scores between groups (gender), gender does have an interaction effect on the correlation between some variables.
Any tips on how to report on this? and does this seem correct? would it be better to actually just run a moderation analysis?
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Do regression not correlation. Test the coefficient of gender differences. Choose a reasonable dependant variable.
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Hello, I am currently using SPSS for my analysis and got stuck with looking for an alternative test for the Two-Way ANOVA for non-parametric data.
I would like to study the effects of two independant variables (both nominal) on a dependent (numeric) variable. For example, how does diagnosis (3 levels) and gender (2 levels) affect the biomarker A.
The collected data of biomarker A is skewed and therefore doesn't follow a normal distribution. Because of this I am not allowed to use the Two-Way ANOVA, is that correct?
Does this assumption of normal distribution still apply with a data set of 130-170 data points or is it neglectible?
I already tried doing Friedman's two-way ANOVA but got an error saying that the ''Friedman's Test can only be performed on two or more ordinal and continuous fields''.
I would be really grateful for suggestions and words of advice! Thank you!
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You may want to consider the R package nparLD for aligned ranks tests.
In attachment an article on Nonparametric Tests for the Interaction in Two-way Factorial Designs Using R.
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COVID-19 is changing the social life of all people. Jumping out of the personal aspect, how does it affect the family as a whole.
Family is regarded as the fundamental structure of the society, will COVID-19 changes the future family structure, unit and model?
How is it affecting gender issues too?
Besides, why is domestic violence increasing? Is psychology and psychiatry playing a role?
reference:
[1] Campbell AM. An increasing risk of family violence during the Covid-19 pandemic: Strengthening community collaborations to save lives.
Forensic Science International: Reports vol. 2 (2020): 100089.
[2]COVID-19: Reducing the risk of infection might increase the risk of intimate partner violence
EClinicalMedicine
[3]The pandemic paradox: The consequences of COVID‐19 on domestic violence
J Clin Nurs
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Dear Dr Sunny Chi Lik Au . See the following useful RG link:
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I am looking for data on Gender Parity/Gender Orientation on Corporate Boards. Can anyone suggest the best databases from where to access comprehensive data on it?
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Please look at the current Chilean democratic changes, new progressivist and young government and a constitutional assembly process. In both instances important efforts have been made to ensure equal representation of men and women, with participation of First Nations and non-binary gender identities too.
I hope this helps.
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Dear Colleagues,
I read in one online source that climate change affects differently men and women? are there scientific explanations for that? Can somebody provide evidence?
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This archaeological problem is Colin Renfrew's well-known sapient behavior paradox. His answer can only be made by using a psychobiological theory of the development of our gender cognition. Theory that must be interdisciplinary through the combined use of the appropriate sciences.
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In my opinion Renfrew establishes the sedentary revolution with the Neolithic, when the cultural revolution occurred with the beginning of the Upper Paleolithic about 42000 BC. C. as he says. In this period an important behavioral change already takes place and we do not have to wait for the Neolithic to appreciate a certain behavioral paradox. If Homo sapiens was already morphologically formed more than 60,000 years ago, why did it take so long to create a culture with the basic characteristics of modernity. Modernity that would become complicated with the development of time and that history shows us: Neolithic, Mesolithic Protohistory, etc.
I think that Renfrew spoke like a good historian, but not like a cognitive scientist, since he was unaware of the psychobiological mechanisms that will guide behavioral development. Only within this partial conception of culture is it possible to speak of the paradox of sapiens, but outside of the simply historical forms there is no such paradox.
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I am researching gender bias in sport media have done a survey which involved 8 sets of 4 images of athletes (4 male and 4 female sets), each being followed up with 3 questions. Participants had to select which image they thought best fit the 3 questions. (So i ended up with 8 answers to each of the questions)
I'm struggling with figuring out how to analyse my data? I need to keep my data in terms of 'amount of times this image was chosen', so i need it to be in whole number (image 1,2,3,4) but everything I try gives me the mean answer from 1-4 across ALL the images for the question.
Questions I am trying to answer are:
Was a certain image chosen more often in the female athlete sets than the male athlete sets (and vice versa)?
Did male/female participants differ from eachother in their responses? (was one gender more likely to select one type of image compared to the other gender)
Happy to answer follow up questions. I feel like the answer is simple but I havent done stat analysis in ages and I just cant think of anything.
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Daniel Wright 8 athletes, different settings/outfits. n around 60 and question is basically just do attitudes towards male and female athletes differ within the particular sport’s community - the survey is only one part of the overall study, but the other parts aren’t relevant to the analysis of this bit.
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I am working on a project where we have company reports with headshots pictures and names of company executives. We are examining individual differences of the executives and would like to use gender or perceived gender as a control variable. Given this is archival data, we don't have the option of collecting self-reported gender. We only have profile pictures and names available.
I'm looking for pointers to papers that have done something similar (more recently is better) or other experience shares on how this might be done while trying to minimize cultural biases of the coders. Our initial thought was to have two raters independently rate the genders and have a third rater settle any ties. Thanks in advance.
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Thank you for the pointer.
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I'd like to ask if any of you can recommend any reading on gender bias in psychological diagnosis. I'm interested in a broad approach to gender - i.e., publications that go beyond the binary division between male and female genders. The issue is quite decently described in terms of differences in diagnoses depending on whether the symptoms are manifested by women or men, but I cannot find any interesting research on the diagnosis/ misdiagnosis of mental disorders for people who identify as, for example, non-binary or transgender. I'd be grateful for any help!
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Sex and gender are two different things. You seem to be conflating them. Sex refers to external reproductive organs usually at birth; gender refers to behavior (masculine/feminine/ gender non-conforming mixtures). Expression of gender identity is a gender behavior but is only meaningful if it refers to previous gender behavior. I do not use the term gender identity for 3 reasons. (1) for a long time "gender identity disorder" was a term used to pathologies transgender people. (2) The term identity in this context is derived from the psychodynamic tradition of Freud and Erikson which has no scientific basis. (3) Identity cannot be operationalized for science because it refers to phenomena that are not observable. Please do not use it. There are some people who mix their gender behaviors who have other problems like depression but this is usually recognized as a secondary cooccurence. The depression is referred to as reactive depression because it is not organic but is a result of rejection by others. Providers who treat such people will typically treat social problems associated with their gender behavior category indicate that if the gender problems are solved through counseling or medical treatment, then the depression goes away.
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I have to conduct the analysis of data collected through phone survey by an external company.
The sample was pre-stratified based on administrative division, gender and area type (rural/urban). In addition, data weighting has been applied on the collected data, with the objective to compensate non-respondents bias; weighting variables have been gender and area type again, as well as age group and education level.
Is it correct to apply both pre-stratification and post data weighting? Do you undersee any concern with the methodology that has been applied?
Thank you for your support!
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Mélanie Broquet, great question!
These are two different things:
Stratification is used to address potential "confounding" issues in your study, such that the variation in the answers given in your survey could be (potentially) explained by the different strata.
What happens is that your stratified sample data may not be proportionally representative of the true stratification in the population. This may or may not be an issue, depending on the overall goal of the study.
Weighting is use to "make sure" that the proportion of each stratum in your data is the same as in the population. This can be done when the data collection is done when the participants were stratified before the beginning of the study (such as in an randomized design) or when stratification was done in the data after collection of the data (such as in an observational study).
Therefore, the goals of performing stratification and weighing are different. Hence, one does not exclude the other.
Finally, what I would like to re-emphasize is what I wrote at the end of the second paragraph: it depends on the overall goal of the study! Generally, in a randomized design we try to obtain strata that are similar in size (i.e., a somewhat balanced design), even if this is NOT representative of the population stratification. In a balanced design, the statistical analysis is "easier", allowing effects to be orthogonal to each other (great feature!).
Let me know if this makes sense to you. Thanks, Nick
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In the Experimental study that included young boys and girls, the treatment is exercises, how do we control biases here?
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@Mazen, do you stratify to ensure you have an equal number of each gender?
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Suppose, from 5 questions, where responses are in 5 points Likert scale (Strongly Agree, Agree, neutral, disagree, Strongly disagree). From these responses, I need to create one variable named gender awareness where there are three categories (Low, Moderate, High). I attempted to review the literature to determine how other researchers classified it, as I believe I require evidence to support this decision, but none of the articles I read specified how they classified the groups. Do any of you have any suggestions for how I should proceed or do you know where I can obtain guidance on how to make this decision?
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One approach would be to conduct taxometric analysis (https://www.amazon.com/Multivariate-Taxometric-Procedures-Distinguishing-Quantitative/dp/B015X4MUCS/ref=sr_1_1) to see if the five questions do differentiate people into three categories, rather than into dimensions. If not, then doing this would be inappropriate. Of course there may be other reasons high the three levels is needed (like the red, green, yellow lights you see on traffic lights and some warning systems). As Bruce Weaver says, tell us why.
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Can anyone refer me to articles on the topic of gender, narrative voice and empathy when watching videos/films. That is, do women or men show higher or lower empathy levels when watching videos/films in first versus third person narrative. Or anything on the topic of gender, narrative voice (third person versus first person narrative) and empathy.
Thank you
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Thank you for the question and for the answer. I find them very interesting. Thank you!
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Several risk factors can enhance the growth of a brain tumor. Like age, gender and work exposure.
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Many thanks for nice question. I think : there are no proved evidences that show any specific factors such as food or diet is associated with the development, management or treatment of brain tumours yet , but surely working with hazardous materials such as heavy metals and other toxins can do it !
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Your research is very interesting. I think that studying it in terms of gender also gives new results because the feelings of women and men are always radically different from each other. Expressions of crying, fear, and affection are observed differently in both sexes.
Have you done any separate research on gender issues related to your topic?
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Actually I will have to... Topic of my habilitation is Education of woman in the developing countries, way to improve the environment...
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Independent Variables:
Sport Type (2 levels)
Gender (3 levels)
Dependent Variable:
1 continuous variable (data from likert scale measure)
AND
Dependent variable:
4 x continuous variables (data from likert scale measure) - four sub-scales.
Thank you
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You could number the Gender and Sports type variables and have interval data for both the Likert, Gender and Sports variables.
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Dear colleagues,
Could anyone point me toward literature on gender euphoria, particularly qualitative studies? I am writing a research paper focusing on the experience of joy that arises from feelings of gender confirmation and congruence. I am especially interested in studying this experience as it occurs across cultures and generations.
Warm Regards,
Hannah Sallmann
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I want do do PhD on gender and education, classroom practices and school environment.
Kindly suggest me.
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As you are planning to do a PhD on gender and education, your deep study will help you get a wonderful and unique title for your thesis.
Best wishes for your PhD.
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I have 2 IV:
- Scale data of skills achievement by our University alumni (They rate from 1 to 7 their acquired skills at University)
- Gender (Already converted it to a dummy variable)
And I have 1 DV:
- Job finding difficulty that has 5 options: (Very Easy, Easy, Neither Easy nor Difficult, Difficult, Very Difficult).
I have 2 questions that I need your assistance with:
1. Can I use a dummy variable with 0, 1, 2, 3, 4, 5 values for my DV?
2. My first IV is not normally distributed, can I still run this regression with it?
I am trying to see the contribution of gender or any specific skills on job finding difficulty.
Please answer as clear and as short as possible.
Thank you!
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You're correct in your comment. However you need to us ordinal logistic regression since your DV is ordinal . Google for further into. Best wishes, David Booth
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I have seen most of the Research papers will calculate Mean for Gender
as Gender is Categorical variable only we can calculate percentage as it comes under Nominal scale
the following article is showing please confirm
How Authoritarian Leadership Affects Employee's Helping Behavior? The Mediating Role of Rumination and Moderating Role of Psychological Ownership"
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yes I think
good work
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Dear researchers,
I'm going to look at gender roles in a few novels from a sociolinguistic standpoint. What approaches do you recommend to analyze such roles?
warm regards,
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Very good question. As I understand that there are six main theoretical approaches include: “(1) the welfare approach; (2) women in development (WID); (3) women and development (WAD); (4) gender and development (GAD); (5) the effectiveness approach (EA); and (6) mainstream gender equality (MGE). You can opt as per you study perspectives.
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I am investigating on boys and girls (15/16yrs) behaviour in the creative process of using technology (electronic music).
Teaching-Frame:
The teacher (me) will give a short introduction about the basic functions of the program using my computer working with a projector.
After that, the students will build groups of 3-5 people*.
I still need to clarify if the group should work on one computer or on more computers using "Soundtrap’s collaboration mode."
Tasks given to the students by the teacher will be very limited*. The groups will work in two sessions each 2 hours during one or two weeks time (depends, if the students have music once or twice a week) and they have to finish a musical composition after that time (= 1 cycle). The project will be repeated in another class in the same age group.
During the project I will write down my observations in form of field notes. Additionally two observers (two fellow students), who take notes with a given focus by me will be present. After each project cycle I will interview 4-5 participating pupils about their attitudes and experiences.
I wonder if I should let my students (for my research project) work totally independently or if I should give tasks like:
Form groups of only your gender, or build mixed gender groups or should they build the groups themselves
Create one signature sound each one of you, and each signature sound has to be heard in your group result
My research questions are:
  1. How can I understand and map the possible gender stereotypes in a music classroom with 15 or 16 year old pupils in a Gymnasium or Efterskole related to music technology? ( I will investigate with a focus group interview after the sessions)
  2. How do girls and boys use and deal with technology in the of music creation?
    1. Are there differences and why?
  3. Which needs have female and male students in this setting to feel comfortable?
  4. Which roles and tasks do students chose to take in the music creation and in the group?
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Excellent question
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I want to test the difference in knowledge, skills and attitude of resp when grouped into age gender, civil status. what stat should I use?
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If you want to split the sample into binary groups (men vs women, old vs young, rich vs. poor) you can use MANCOVA. If you want to keep it as continuous variables (precise age, precise income) you should use regression.
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Hello,
We are looking for someone who is willing to help with reporting the stats of our project regarding age, gender, personality, and friendship. Please leave your email if of interests.
Best wishes,
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I am trying to relate Climate issues with migration and gender marginilization. I am wondering if there are any technical calculations or index that has been used before to quantify or measure the impact - the parameter may be economic, or any other. Depending on how it can be quantified, I would shape my research.
I am open to ideas
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Water and climate-related migration intersection with UN Sustainable Development Goal(s) agenda mainly: SDG 6: Clean water and sanitation, SDG 5: Gender Equality and SDG 16: Institutions and Policies and SDG17: Partnership models.
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I need to find association between gender and tibiofemural distance which statistical test will be appropriate in the scenario?
Also which test to be performed if I need to find an association between a test( positive or negative) and type of tibia( class I,II, iii)
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Descriptive statistics
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I have a small but significant relationship between pain scores and risk of a certain condition (R^2=0.057, p=0.039).
When I include age and gender as covariates, the model loses all significance (R^2=0.043, p=0.15).
This suggests to me that age and/or gender explain at least as much of the variance in pain scores that risk does.
However, when the univariate regressions just of age and gender show no relationship at all (age R^2=0.017, p=0.8, gender R^2=0.005, p=0.4)
I cant quite wrap my head around what the potential relationships between the covariates might be.
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There might be a bit of collinearity indeed but that's normal if not all covariates/independent variables are perfectly balanced (I can imagine pain score to vary with age, and maybe gender).
  • One important question would be: does it matter? Given that the model without age and gender only explains 5.7% of the variance in the response, and the p-value is borderline, the result is already saying that pain scores don't say very much about the outcome... (Note: p-values also have uncertainty although it is not reported)
  • Collinearity has been almost "demonised" for a long time (I have been guilty too), but some have suggested recently that we should consider it part of reality (and increased uncertainty, reduced statistical significance) rather than trying to get rid of it...
Hope that helps making sense of collinearity and the result...
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HI there,
I am looking to examine whether a categorical variable (e.g., gender) moderates the difference in food intake between two time-points. How can I do this?
Could I compute a change score, and compare the means for that change score between genders?
Or could I regress the score at the second time point on gender and control for the first time point to indicate the impact on the change?
Thanks a lot,
Esther
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Hello Esther,
If you believe that difference scores (e.g., time2 measure - time 1 measure) are error-free, then feel free to compute difference scores and compare them statistically between gender groups (ordinary independent t test could work). However, note that gender may be a proxy for any number of confounding variables which themselves may be the "actual" moderator.
An alternative design, which fares a bit better if measurement error is a possibility, is to use time 1 values as a covariate, and run a simple ancova on the time 2 scores.
Good luck with your work.
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Hi,
I'm currently working on a master thesis based on a research.
I have 3 groups:
1. Healthy controls (N=211)
2. Patients with disease type A. (N=75)
3. Patients with disease type B. (N=47)
I want to know whether these groups differ from each other significantly in terms of gender ratio (male : female). I would need 3 seperate p values, so a comparison of patient group with disease type A compared to healthy controls; patient group with disease type B compared healthy controls and patient group with disease type A compared to patient group with disease type B.
I'm unsure what statistical test to use to determine this (I personally think either a independent sample t test or a Fishers exact test). Any help would be much appreciated. If further information is required, I'll be happy to share.
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Pepijn Hesselink , I think your question has mislead commentators. In your comment, you say you have a collection of variables. Is your goal to explore is this collection of variables differs among those three groups? I am also assuming that this collection of variables are associated with each other. If this is true, it would be better to start a new question.
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Dear scholars,
I have an interest in building a research area touching on gender and its impact on leadership & management styles/practices.
Any guidance on how to approach the subject matter? In addition, are there theoretical approaches aligned to gender, leadership, and management?
Any willing mentors?
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Hi Lilian,
there is a substantial literature on gender and leadership, both in terms of emergence (who becomes a leader) and effectiveness (how well does the leader perform).
I suggest checking out the work by Alice Eagly and colleagues. Other meta-analyses might also help you get a better overview of the existing literature. Here are some suggested reads:
Eagly, A. H., & Johnson, B. T. (1990). Gender and leadership style: A meta-analysis. Psychological bulletin, 108(2), 233.
Eagly, A. H., Makhijani, M. G., & Klonsky, B. G. (1992). Gender and the evaluation of leaders: A meta-analysis. Psychological bulletin, 111(1), 3.
Eagly, A. H., Karau, S. J., & Makhijani, M. G. (1995). Gender and the effectiveness of leaders: a meta-analysis. Psychological bulletin, 117(1), 125.
Eagly, A. H., & Karau, S. J. (1991). Gender and the emergence of leaders: A meta-analysis. Journal of personality and social psychology, 60(5), 685.
Paustian-Underdahl, S. C., Walker, L. S., & Woehr, D. J. (2014). Gender and perceptions of leadership effectiveness: A meta-analysis of contextual moderators. Journal of applied psychology, 99(6), 1129.
A theory that is quite often utilized in this context is Eagly's (1987) gender role theory, according to which societies have inherent expectations toward men and women. Women are generally expected to be more communal (e.g. caring) and men to be agentic (e.g. take charge or intiative). This can obviously vary between different cultures. This theory might explain why the same leader behavior can be appraised differently by followers depending on the gender of the leader.
Eagly, A. (1987). Sex differences in social behavior: A social role interpretation. Hillsdale, NJ: Erlbaum.
I hope this helps.
Nils
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