Methodology Helpdesk

The methods helpdesk is now offering the below expertise:

• Anne de la Croix

  With a background in linguistics, I feel most at home when analysing written (or transcribed) texts and/or conversations. Gathering this data is something I can help you with: how to conduct a ‘good’ interview or focus group? I like using prompts or techniques to really optimise the conversations that lead to a rich data set. When it comes to analysis, I have experience with qualitative research approaches that aim to unveil themes in the data, such as Thematic/template/content analysis. But I have also done many studies in which the focus lies on the use of language or on the structure of interactions, such as Conversation Analysis and (Critical/Foucauldian) Discourse Analysis. Qualitative research asks for teamwork, for openness to the idea of subjectivity in research, and for much reflection on the process itself. I can help with these themes and can point you in the right direction through using my extensive library.

  e-mail: a.delacroix@amsterdamumc.nl

• Melanie Ehren

  I’m happy to offer my expertise in realist evaluation and particularly in policy theory reconstruction. Those of you who are not familiar with this methodology, realist evaluation is a term used for theory-driven evaluation methods of programmes and policies which aim to answer questions such as what works, for whom, under which conditions and why? An example of my work are the various policy theory reconstructions for the Dutch and English Inspectorate of Education that describe the assumptions underpinning their inspection frameworks and how these are expected to lead to school and system improvement. In further empirical (qualitative and quantitative) work we have tested these assumptions. The benefit of the approach is its value for generating in-depth insights about the specific workings of a programme and policy and testing the assumptions of those who are responsible for the programme or policy. For further background, see:  https://www.degeval.org/fileadmin/ZfEv/Heft_2/2021/06_Ehren.pdf 

  e-mail: m.c.m.ehren@vu.nl

• Ina Koning

  I’m happy to offer my expertise in experimental studies, community-based / environmental interventions in specific, where stakeholders are engaged throughout the process. This may be evaluated in a quasi-experimental design or randomised cluster trial, applying quantitative and qualitative methods. Also, my experience relates to all phases of systematic intervention planning; from needs assessment to implementation and evaluation. An example of such a project is ‘program LEF’ (https://www.lef-edvo.nl/). In this program we investigated the effectiveness of a community-based intervention on adolescents’ alcohol use. I usually integrate longitudinal data analysis in Mplus with a more descriptive analysis of the implementation process. Last, my expertise revolves around the topics digital media use (addiction), substance use, parenting and interventions. Let me know if you have any questions!

  e-mail: h.m.koning@vu.nl

• Cor van Montfort

  I am a senior researcher at de Vrije Universiteit Amsterdam, member of the National Education Council and research fellow at Tilburg University. In research, I currently focus on the relation between good governance, public accountability and the quality of education (Vrije Universiteit Amsterdam), as well as on public-private partnerships for livable cities (Tilburg University). Together with research groups from all over the world I am working on an edited volume about this topic. During my career, I have published about public private partnerships, public entrepreneurship, public value management, good governance and public accountability in different policy domains like pension provision, social security, water management, social housing and education. In the past years, I performed several research projects and advisory projects on request of the Dutch government and the Dutch parliament on the topics of social security, good governance, social housing and education.

  e-mail: c.j.van.montfort@vu.nl

• Tom Stolp

  My expertise is causal inference and predictive modelling. In particular, I answer questions that address whether treatments or policies have a causal impact on some outcome of interest – e.g. test scores, labour supply or educational choice. The crux of these methodologies is to predict what would have happened in the case a treatment or policy had not occurred – the counterfactual. Then, the observed outcome – with treatment - and the estimated counterfactual – without treatment - can be compared to identify the treatment effect. To do so, I use different statistical methods such as propensity score matching, difference-in-difference, instrumental variables, multilevel modelling, regression discontinuity. In addition, a novel way of estimating causal effects is by use of machine learning. An example is a recent study, in which I examine whether a wage increase for primary schools in Amsterdam causes an increase in teacher supply. Here, the machine learning algorithm constructs what would have happened to Amsterdam teacher supply had not occurred. By comparing the difference between the actual development of teacher staffing – with wage increase – to the estimated counterfactual development – without wage increase -, the causal effect of the treatment is identified.

  e-mail: t.h.stolp@vu.nl

• Anne Tharner

  I would like to offer my expertise in observation of parent-child interactions in scientific research. I am a certified coder for several coding systems for parent-child attachment (Strange Situation Procedure) and parent-child interactions (e.g., Coding Interactive Behavior scale) and parenting behaviour (e.g., Emotional Availability Scales, Atypical Maternal Behavior Instrument for Assessment and Classification). I have coded many observations myself and have advised several research projects in setting up observations and training students and researchers in conducting and coding parent-child interactions. Don’t hesitate to contact me!

  e-mail: a.tharner@vu.nl

• Melvin Vooren

  I am happy to offer my expertise in experimental and quasi-experimental policy evaluation, including RCTs, instrumental variables, regression discontinuity designs, differences-in-differences, and statistical matching. I can also offer my help with predictive modelling using machine learning techniques. In my work, I apply quantitative research on large data sets, including microdata from Statistics Netherlands. I am particularly interested in following subjects over time using longitudinal administrative data, for instance with survival analysis. I also have experience with meta-analysis, in particular meta-regression models. I am especially interested in statistical techniques to correct for publication bias.

  e-mail: m.vooren@vu.nl